Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010126
Linda Rodriguez, Ivan Ponce, H. Espitia
This paper proposes a fuzzy inference system for color manipulation in digital images in order to modify its artistic style, in this case the art form called psychedelic. The proposed fuzzy logic system, modeled by sets and fuzzy inference rules, generating images with colors characteristic of this type of art. In the second part fits inference system with the proposed technique; proposed an optimization algorithm based on particle swarms, finally showing improved results.
{"title":"Particle swarm optimization used in a fuzzy inference system for color modification from digital images to an psychedelic artistic style","authors":"Linda Rodriguez, Ivan Ponce, H. Espitia","doi":"10.1109/STSIVA.2014.7010126","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010126","url":null,"abstract":"This paper proposes a fuzzy inference system for color manipulation in digital images in order to modify its artistic style, in this case the art form called psychedelic. The proposed fuzzy logic system, modeled by sets and fuzzy inference rules, generating images with colors characteristic of this type of art. In the second part fits inference system with the proposed technique; proposed an optimization algorithm based on particle swarms, finally showing improved results.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"39 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128844803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010124
Darwin Omar Alulema Flores, F. Pineda-López, Edwin Leonardo Garcia Aucatoma, Fabian Eduardo Izquierdo Cordova
It has been determined that the sessions with EMDR methodology applied in a digital form, allowing the psychotherapist treating patients with psychological disorders, and whereas there is currently no way to provide the methodology in this way, the next project is focused on the development a prototype that generates visual, auditory and tactile sequences used by this methodology in a manual or automatic way to provide therapy sessions to Psychotherapist. The control software for the prototype was developed on the Android platform to be deployed on mobile devices, allowing the Psychotherapist from your smartphone or tablet to control the type and speed of the sequences in all modules, the kind of sound in the ear module and the duration of the vibration on the tactile module. Additional software includes a database to record patient data. The interaction of the user that uses Android device psychotherapist and the patient is given by an IOIO board and a hardware adapted for the purpose. Psychotherapists who used the EMDR system showed a reduction in treatment times of 20-30 minutes per session. Psychotherapists reported that physical fatigue was reduced by a margin of 90 percent and mental fatigue by 75 percent in the traditional way of providing EMDR patients, allowing more consecutive sessions provide the same quality of treatment initiation to the end of his workday.
{"title":"Automated system on android platform for use in the implementation psychotherapeutic technical EMDR","authors":"Darwin Omar Alulema Flores, F. Pineda-López, Edwin Leonardo Garcia Aucatoma, Fabian Eduardo Izquierdo Cordova","doi":"10.1109/STSIVA.2014.7010124","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010124","url":null,"abstract":"It has been determined that the sessions with EMDR methodology applied in a digital form, allowing the psychotherapist treating patients with psychological disorders, and whereas there is currently no way to provide the methodology in this way, the next project is focused on the development a prototype that generates visual, auditory and tactile sequences used by this methodology in a manual or automatic way to provide therapy sessions to Psychotherapist. The control software for the prototype was developed on the Android platform to be deployed on mobile devices, allowing the Psychotherapist from your smartphone or tablet to control the type and speed of the sequences in all modules, the kind of sound in the ear module and the duration of the vibration on the tactile module. Additional software includes a database to record patient data. The interaction of the user that uses Android device psychotherapist and the patient is given by an IOIO board and a hardware adapted for the purpose. Psychotherapists who used the EMDR system showed a reduction in treatment times of 20-30 minutes per session. Psychotherapists reported that physical fatigue was reduced by a margin of 90 percent and mental fatigue by 75 percent in the traditional way of providing EMDR patients, allowing more consecutive sessions provide the same quality of treatment initiation to the end of his workday.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121155592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010155
S. Rodriguez, S. R. M. Gutierrez, V. A. E. Jaramillo
The Gas Electron Multiplier (GEM) is one of the most popular and powerful technologies for gaseous ionization detectors used in high energy physics, medical physics and other applications. One of the fundamental elements of a GEM is foils with micro perforations; the qualities of such perforations are basic for an optimal performance of the GEM. In this work we study different computational methods (implemented in java programming language), in order to determine the quality of GEM-foils from high resolution images of the foils. This computational method will provide an automatic and high precision alternative to a procedure which, at the moment, is very expensive, slow and imprecise, being a limitation for the development and application of this important technology of detectors.
{"title":"Optical quality control of Gas Electron Multiplier foils","authors":"S. Rodriguez, S. R. M. Gutierrez, V. A. E. Jaramillo","doi":"10.1109/STSIVA.2014.7010155","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010155","url":null,"abstract":"The Gas Electron Multiplier (GEM) is one of the most popular and powerful technologies for gaseous ionization detectors used in high energy physics, medical physics and other applications. One of the fundamental elements of a GEM is foils with micro perforations; the qualities of such perforations are basic for an optimal performance of the GEM. In this work we study different computational methods (implemented in java programming language), in order to determine the quality of GEM-foils from high resolution images of the foils. This computational method will provide an automatic and high precision alternative to a procedure which, at the moment, is very expensive, slow and imprecise, being a limitation for the development and application of this important technology of detectors.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127548361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.33975/RIUQ.VOL28N1.30
L. Díaz, Y. Morales, C. Torres
Currently, many patients are interested in esthetic dentistry treatments for various reasons: from the search for personal satisfaction, up to needs labor type. The esthetic dentistry reference in our society is determined by several factors, including one that produces more dissatisfaction is abnormal tooth color or that does not meet the patient's expectations. For this reason it has been designed and implemented an algorithm in MATLAB that captures, digitizes, pre-processing and analyze dental imaging by allowing to evaluate the degree of bleaching caused by the use of mouthwash. The samples analyzed were human teeth extracted, which were subjected to different concentrations of mouthwash of several brands or manufacturers that offer teeth whitening when using these products, different concentrations of hydrogen peroxide were also used because this is the component principal in whitening products.
{"title":"Study of the temporal evolution of whitening in teeth undergoing mouthwashes using digital image processing","authors":"L. Díaz, Y. Morales, C. Torres","doi":"10.33975/RIUQ.VOL28N1.30","DOIUrl":"https://doi.org/10.33975/RIUQ.VOL28N1.30","url":null,"abstract":"Currently, many patients are interested in esthetic dentistry treatments for various reasons: from the search for personal satisfaction, up to needs labor type. The esthetic dentistry reference in our society is determined by several factors, including one that produces more dissatisfaction is abnormal tooth color or that does not meet the patient's expectations. For this reason it has been designed and implemented an algorithm in MATLAB that captures, digitizes, pre-processing and analyze dental imaging by allowing to evaluate the degree of bleaching caused by the use of mouthwash. The samples analyzed were human teeth extracted, which were subjected to different concentrations of mouthwash of several brands or manufacturers that offer teeth whitening when using these products, different concentrations of hydrogen peroxide were also used because this is the component principal in whitening products.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130013652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010129
N. García, J. C. Vásquez-Correa, J. Vargas-Bonilla, J. D. Arias-Londoño, J. Orozco-Arroyave
The estimation of the fundamental frequency (F0) in speech is a very important task that has been addressed by many researchers. F0 estimation can be used to separate two kind of frames from an utterance, those where the vocal folds vibrate (voiced sounds) and those where not (unvoiced sounds). The methods used to estimate F0 are affected by the presence of additive noise in recordings made in non-controlled environments, however, there are different techniques to mitigate the effect of such noise and Speech Enhancement (SE) has proven to be one of the most effective ones. This article presents results of the evaluation of the effects of noise and SE algorithms on the detection of F0 and the signal segmentation in voiced/unvoiced segments. We performed experiments with signals artificially contaminated with two different kinds of noise, White Gaussian Noise (WGN) and background noise recorded at a cafeteria (Cafeteria babble), subsequently, the signals are processed with SE algorithms of four different classes: Wiener Filter, Spectral Subtraction, Statistical-Model Based and Sub-space algorithms. Two different kind of error metrics are considered: Gross Pitch Error and Voicing Determination Error. The results show that only the sub-space approach improves the performance in the detection of F0 and the signal segmentation in voiced/unvoicd segments.
{"title":"Evaluation of the effects of speech enhancement algorithms on the detection of fundamental frequency of speech","authors":"N. García, J. C. Vásquez-Correa, J. Vargas-Bonilla, J. D. Arias-Londoño, J. Orozco-Arroyave","doi":"10.1109/STSIVA.2014.7010129","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010129","url":null,"abstract":"The estimation of the fundamental frequency (F0) in speech is a very important task that has been addressed by many researchers. F0 estimation can be used to separate two kind of frames from an utterance, those where the vocal folds vibrate (voiced sounds) and those where not (unvoiced sounds). The methods used to estimate F0 are affected by the presence of additive noise in recordings made in non-controlled environments, however, there are different techniques to mitigate the effect of such noise and Speech Enhancement (SE) has proven to be one of the most effective ones. This article presents results of the evaluation of the effects of noise and SE algorithms on the detection of F0 and the signal segmentation in voiced/unvoiced segments. We performed experiments with signals artificially contaminated with two different kinds of noise, White Gaussian Noise (WGN) and background noise recorded at a cafeteria (Cafeteria babble), subsequently, the signals are processed with SE algorithms of four different classes: Wiener Filter, Spectral Subtraction, Statistical-Model Based and Sub-space algorithms. Two different kind of error metrics are considered: Gross Pitch Error and Voicing Determination Error. The results show that only the sub-space approach improves the performance in the detection of F0 and the signal segmentation in voiced/unvoicd segments.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124607921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010183
Andres Felipe Lopez Lopera, Hernán Darío Vargas Cardona, G. Daza-Santacoloma, Mauricio A Álvarez, Á. Orozco
The Magnetic Diffusion Images or Diffusion Weighted Images (DWIs) are based on Magnetic Resonance (MR) techniques to study water particles' diffusion in human brains. These images are used for determining which neuron pathways were used for the communication among the principal regions of the brain by estimating the diffusion tensors (DTs). DTs contain all the information of water diffusion for each individual voxel of the image. The filtering of these images is relevant to remove the level of noise of each image and improve the DTs estimation. Moreover, the smoothing methods may be used to reduce noise in medical images. However, certain smoothing filters may blur important features such as edges and also affect structures, so it is essential to preserve the fine features using anisotropic diffusion filtering. Therefore, we need to preprocess this type of brain images by removing noise, smoothing surfaces and enhancing edges, are necessary to improve the results of estimating the DTs. This paper formalizes and compares the advantages and disadvantages obtained by applying different kinds of preprocessing techniques for removing noise, smoothing surfaces and enhancing edges techniques include Median Filter (MF), Perona-Malik algorithm and Gaussian filter (GF). Then, in order to determine the potential benefits of the mentioned pre-processing, the DTs are estimated with and without using the filter stage. In addition, several metrics are used for the evaluation and comparison of the DWI preprocessing methods. Finally, we discuss the quality of these methods and we also define what are the appropriate conditions for each preprocessing method.
{"title":"Comparison of preprocessing methods for diffusion tensor estimation in brain imaging","authors":"Andres Felipe Lopez Lopera, Hernán Darío Vargas Cardona, G. Daza-Santacoloma, Mauricio A Álvarez, Á. Orozco","doi":"10.1109/STSIVA.2014.7010183","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010183","url":null,"abstract":"The Magnetic Diffusion Images or Diffusion Weighted Images (DWIs) are based on Magnetic Resonance (MR) techniques to study water particles' diffusion in human brains. These images are used for determining which neuron pathways were used for the communication among the principal regions of the brain by estimating the diffusion tensors (DTs). DTs contain all the information of water diffusion for each individual voxel of the image. The filtering of these images is relevant to remove the level of noise of each image and improve the DTs estimation. Moreover, the smoothing methods may be used to reduce noise in medical images. However, certain smoothing filters may blur important features such as edges and also affect structures, so it is essential to preserve the fine features using anisotropic diffusion filtering. Therefore, we need to preprocess this type of brain images by removing noise, smoothing surfaces and enhancing edges, are necessary to improve the results of estimating the DTs. This paper formalizes and compares the advantages and disadvantages obtained by applying different kinds of preprocessing techniques for removing noise, smoothing surfaces and enhancing edges techniques include Median Filter (MF), Perona-Malik algorithm and Gaussian filter (GF). Then, in order to determine the potential benefits of the mentioned pre-processing, the DTs are estimated with and without using the filter stage. In addition, several metrics are used for the evaluation and comparison of the DWI preprocessing methods. Finally, we discuss the quality of these methods and we also define what are the appropriate conditions for each preprocessing method.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116525429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010180
Cristian A. Torres-Valencia, G. Daza-Santacoloma, A. Orozco-Gutierrez
Deep Brain Stimulation (DBS) is a clinical treatment for Parkinson disease and has demonstrated the effective control of some of the symptoms related with Parkinson. DBS consist in the implantation of a neurostimulator into a region of the brain such as the subthalamic nucleus, the internal globus pallidus, etc. The electrodes are configured with a desired electric pulse in order to achieve the neural activation of the objective regions. Parameters of the stimulation pulse are experimentally adjusted for the neurologist during several sessions. In recent years, some efforts has been realized in order to facilitate the selection of the optimal parameters for DBS therapy without the experimental process, using head models that includes the electrical properties and geometry of the different brain structures in which the electric propagation is desired. The large variety of electromagnetic phenomena can all be described by the Maxwell's equations, which are also the basis for deep brain stimulation modelling. In particular, the Laplace equation is well suited for computing the electric propagation due DBS. For solving the Laplace equation in complex geometries is used the finite element method (FEM), which allows to compute of a numerical solution of differential equations applied over several domains by the creation of a structured mesh. The state of art works presented in the context of DBS modelling such as [1] [2] commonly uses a commercial software for FEM calculation. Since there is no way to measure the potentials directly from the brain during DBS, propagation models of the brain must be builded to determine the electric propagation. Nowadays, several GNU libraries for FEM computing are available. This work addresed the use of FEnICS library for C++ and phyton for solving the electric propagation in 2D and 3D geometrical models. With this in mind, we are interested in estimating the voltage propagation, around the DBS lead, in a particular area of the brain. Results show that the GNU libraries are well suited for FEM-DBS modelling in contrast to the obtained results using commercial software found in the literature.
{"title":"Electric propagation modeling of Deep Brain Stimulation (DBS) using the finite element method (FEM)","authors":"Cristian A. Torres-Valencia, G. Daza-Santacoloma, A. Orozco-Gutierrez","doi":"10.1109/STSIVA.2014.7010180","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010180","url":null,"abstract":"Deep Brain Stimulation (DBS) is a clinical treatment for Parkinson disease and has demonstrated the effective control of some of the symptoms related with Parkinson. DBS consist in the implantation of a neurostimulator into a region of the brain such as the subthalamic nucleus, the internal globus pallidus, etc. The electrodes are configured with a desired electric pulse in order to achieve the neural activation of the objective regions. Parameters of the stimulation pulse are experimentally adjusted for the neurologist during several sessions. In recent years, some efforts has been realized in order to facilitate the selection of the optimal parameters for DBS therapy without the experimental process, using head models that includes the electrical properties and geometry of the different brain structures in which the electric propagation is desired. The large variety of electromagnetic phenomena can all be described by the Maxwell's equations, which are also the basis for deep brain stimulation modelling. In particular, the Laplace equation is well suited for computing the electric propagation due DBS. For solving the Laplace equation in complex geometries is used the finite element method (FEM), which allows to compute of a numerical solution of differential equations applied over several domains by the creation of a structured mesh. The state of art works presented in the context of DBS modelling such as [1] [2] commonly uses a commercial software for FEM calculation. Since there is no way to measure the potentials directly from the brain during DBS, propagation models of the brain must be builded to determine the electric propagation. Nowadays, several GNU libraries for FEM computing are available. This work addresed the use of FEnICS library for C++ and phyton for solving the electric propagation in 2D and 3D geometrical models. With this in mind, we are interested in estimating the voltage propagation, around the DBS lead, in a particular area of the brain. Results show that the GNU libraries are well suited for FEM-DBS modelling in contrast to the obtained results using commercial software found in the literature.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122290210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010177
J. Gomez, S. Bromberg
This paper presents the design, development and testing of an application to recognize regulatory traffic signs vertically installed on Colombian roads. The application is conceived as a module of a driver assistance system under development, and an autonomous vehicle adapted to the local infrastructure. The application uses Support Vector Machines which are trained and tested with official synthetic images provided by the National Ministry of Transport. These images are modified with chromatic and geometric changes to emulate fluctuations in illumination, vantage point, and ageing. Resulting images are resized to 48 × 48 pixels, and the raw intensity planes in the Hue-Saturation-Intensity color model are reshaped to obtain feature vectors with 2304 attributes each. In total, forty seven binary classifiers were trained under a one-versus-all classification scheme. These classifiers were directly combined into a multi-class classification system. This paper reports the methodology used to collect the data, configure, train, and evaluate the performance of classifiers working isolated and collectively.
{"title":"Design and evaluation of a traffic sign recognition system based on Support Vector Machines","authors":"J. Gomez, S. Bromberg","doi":"10.1109/STSIVA.2014.7010177","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010177","url":null,"abstract":"This paper presents the design, development and testing of an application to recognize regulatory traffic signs vertically installed on Colombian roads. The application is conceived as a module of a driver assistance system under development, and an autonomous vehicle adapted to the local infrastructure. The application uses Support Vector Machines which are trained and tested with official synthetic images provided by the National Ministry of Transport. These images are modified with chromatic and geometric changes to emulate fluctuations in illumination, vantage point, and ageing. Resulting images are resized to 48 × 48 pixels, and the raw intensity planes in the Hue-Saturation-Intensity color model are reshaped to obtain feature vectors with 2304 attributes each. In total, forty seven binary classifiers were trained under a one-versus-all classification scheme. These classifiers were directly combined into a multi-class classification system. This paper reports the methodology used to collect the data, configure, train, and evaluate the performance of classifiers working isolated and collectively.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125682100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010176
D. Chaves, M. Trujillo, J. Barraza
Separation of touching char particles is required for measuring morphological characteristics. In this paper, a segmentation approach for touching char particles is presented. The proposed approach is fourfold. Firstly, contours are extracted. Secondly, concave points are identified by the means of measuring concavity using gradient directions at contour points. Concave points are candidates of touching point. Thirdly, separation lines are identified using location, length, blur and area. Fourthly, a decision criterion is derived for deciding whether to split a particle or not. Coal samples, from three Colombian regions (Antioquia, Cundinamarca, and Valle) and blend coals 50%-50% were devolatilised and chars were obtained. The proposed approach was evaluated using 180 images of char particles and compared to the Watershed algorithm. The evaluation was twofold: quantifying the accuracy in identifying touching particles and measuring the separation quality. An expert criterion was used, as a ground truth, for qualitative evaluations. A good agreement between the visual judgement and automatic results was obtained, using the proposed approach.
{"title":"A segmentation approach for touching char particles","authors":"D. Chaves, M. Trujillo, J. Barraza","doi":"10.1109/STSIVA.2014.7010176","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010176","url":null,"abstract":"Separation of touching char particles is required for measuring morphological characteristics. In this paper, a segmentation approach for touching char particles is presented. The proposed approach is fourfold. Firstly, contours are extracted. Secondly, concave points are identified by the means of measuring concavity using gradient directions at contour points. Concave points are candidates of touching point. Thirdly, separation lines are identified using location, length, blur and area. Fourthly, a decision criterion is derived for deciding whether to split a particle or not. Coal samples, from three Colombian regions (Antioquia, Cundinamarca, and Valle) and blend coals 50%-50% were devolatilised and chars were obtained. The proposed approach was evaluated using 180 images of char particles and compared to the Watershed algorithm. The evaluation was twofold: quantifying the accuracy in identifying touching particles and measuring the separation quality. An expert criterion was used, as a ground truth, for qualitative evaluations. A good agreement between the visual judgement and automatic results was obtained, using the proposed approach.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131462041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-09-01DOI: 10.1109/STSIVA.2014.7010154
E. Zurek, A. M. R. Gamarra, G. J. R. Escorcia, Carlos A. Gutiérrez, H. Bayona, R. Pérez, Xavier García
This article presents results of the recognition process of acoustic fingerprints from a noise source using spectral characteristics of the signal. Principal Components Analysis (PCA) is applied to reduce the dimensionality of extracted features and then a classifier is implemented using the method of the k-nearest neighbors (KNN) to identify the pattern of the audio signal. This classifier is compared with an Artificial Neural Network (ANN) implementation. It is necessary to implement a filtering system to the acquired signals for 60Hz noise reduction generated by imperfections in the acquisition system. The methods described in this paper were used for vessel recognition.
{"title":"Spectral analysis techniques for acoustic fingerprints recognition","authors":"E. Zurek, A. M. R. Gamarra, G. J. R. Escorcia, Carlos A. Gutiérrez, H. Bayona, R. Pérez, Xavier García","doi":"10.1109/STSIVA.2014.7010154","DOIUrl":"https://doi.org/10.1109/STSIVA.2014.7010154","url":null,"abstract":"This article presents results of the recognition process of acoustic fingerprints from a noise source using spectral characteristics of the signal. Principal Components Analysis (PCA) is applied to reduce the dimensionality of extracted features and then a classifier is implemented using the method of the k-nearest neighbors (KNN) to identify the pattern of the audio signal. This classifier is compared with an Artificial Neural Network (ANN) implementation. It is necessary to implement a filtering system to the acquired signals for 60Hz noise reduction generated by imperfections in the acquisition system. The methods described in this paper were used for vessel recognition.","PeriodicalId":114554,"journal":{"name":"2014 XIX Symposium on Image, Signal Processing and Artificial Vision","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124106033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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