Pub Date : 2012-11-12DOI: 10.1109/STSIVA.2012.6340596
Sujeimar Arroyave Restrepo, Juan Camilo Herrera Pineda
The main idea of this paper is to present a general description of the project “path planning applied to a mobile robot GBot”, which includes items such as the approach taken, the implemented techniques in areas like digital image processing and path planning in mobile robots. Furthermore, there is a section that presents the performance and a small analysis of the implemented system. The problem treated in this paper, is based on the need to develop a system that allows to a robot to go from a starting point to an end point. Without mishaps or collisions through the shortest possible route between two points. To achieve this, we use color segmentation as main technique of digital image processing. While in path planning, you will found within this work that the main tool is the Voronoi diagram combined with the search Dijkstra algorithm.
{"title":"Path planning applied to the mobile robot GBot","authors":"Sujeimar Arroyave Restrepo, Juan Camilo Herrera Pineda","doi":"10.1109/STSIVA.2012.6340596","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340596","url":null,"abstract":"The main idea of this paper is to present a general description of the project “path planning applied to a mobile robot GBot”, which includes items such as the approach taken, the implemented techniques in areas like digital image processing and path planning in mobile robots. Furthermore, there is a section that presents the performance and a small analysis of the implemented system. The problem treated in this paper, is based on the need to develop a system that allows to a robot to go from a starting point to an end point. Without mishaps or collisions through the shortest possible route between two points. To achieve this, we use color segmentation as main technique of digital image processing. While in path planning, you will found within this work that the main tool is the Voronoi diagram combined with the search Dijkstra algorithm.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114351167","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 : 2012-11-12DOI: 10.1109/STSIVA.2012.6340601
S. E. Molina, L. Matos, C. Torres
In this paper shows the analysis of the implementation of a adapted filter to a chirp signal in the domain of the optimal order of the FrFT. Here express the equations for a chirp signal receptor in the frequency domain and a general equation in the Fourier fractional domain using the Phase stationary principle (PSP), with the objective of expose the adapted filter limitations, describe the affecting parameters the chirp signal and demonstrate the better performance through use of adapted filter in the Fourier fractional domain of optimal order for special cases.
{"title":"Adapted filters in the domain of the fractional fourier transform","authors":"S. E. Molina, L. Matos, C. Torres","doi":"10.1109/STSIVA.2012.6340601","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340601","url":null,"abstract":"In this paper shows the analysis of the implementation of a adapted filter to a chirp signal in the domain of the optimal order of the FrFT. Here express the equations for a chirp signal receptor in the frequency domain and a general equation in the Fourier fractional domain using the Phase stationary principle (PSP), with the objective of expose the adapted filter limitations, describe the affecting parameters the chirp signal and demonstrate the better performance through use of adapted filter in the Fourier fractional domain of optimal order for special cases.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"46 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134092591","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 : 2012-11-12DOI: 10.1109/STSIVA.2012.6340579
L. Garcés, H. Gualdron, A. Gómez
The cell analysis, usually performed by specialists to diagnose a patient, has drawbacks. Since the sample has a short biological life cycle; moreover, it is prone to alterations by inappropriate handling. One solution to this problem is the digitalization and virtualizations of slides. The group of Development and Technological Innovation-DIT- of BIOSYS LTDA Company is developing a technique. This consists of slide digitization under a microscope (several shots of images of cell fields) and subsequent virtualization, while the user (Bacteriologist or technologist, etc.) performs their daily work. Due to blurring (caused by slide movement) at moment of reading the slide, not all pictures can be used for slide virtualization. For this reason, we must choose the image of each cell field, with less blur. This work presents the results of the implementation of a direct method based on the application of the Haar Wavelet Transform, to detect and eliminate blurred images which are not necessary in the creation of a virtual slide. The results were obtained from a database with 20 sets of cell fields, which for each field were available 15 images with different focus conditions.
{"title":"Elimination of blurred images of cellular fields to virtualize a slide","authors":"L. Garcés, H. Gualdron, A. Gómez","doi":"10.1109/STSIVA.2012.6340579","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340579","url":null,"abstract":"The cell analysis, usually performed by specialists to diagnose a patient, has drawbacks. Since the sample has a short biological life cycle; moreover, it is prone to alterations by inappropriate handling. One solution to this problem is the digitalization and virtualizations of slides. The group of Development and Technological Innovation-DIT- of BIOSYS LTDA Company is developing a technique. This consists of slide digitization under a microscope (several shots of images of cell fields) and subsequent virtualization, while the user (Bacteriologist or technologist, etc.) performs their daily work. Due to blurring (caused by slide movement) at moment of reading the slide, not all pictures can be used for slide virtualization. For this reason, we must choose the image of each cell field, with less blur. This work presents the results of the implementation of a direct method based on the application of the Haar Wavelet Transform, to detect and eliminate blurred images which are not necessary in the creation of a virtual slide. The results were obtained from a database with 20 sets of cell fields, which for each field were available 15 images with different focus conditions.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133298512","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 : 2012-11-12DOI: 10.1109/STSIVA.2012.6340558
S. Bedoya-Jaramillo, E. Belalcázar-Bolaños, T. Villa-Cañas, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla
Emotional states produce physiological alterations in the vocal tract introducing variability in the acoustic parameters of speech. Emotion recognition in speech can be used in human-machine interaction applications, speaker verification, analysis of neurological disorders and psychological diagnostic tools. This paper proposes the use of Mel Frequency Cesptral Coefficients (MFCC) for automatic detection of emotions in running speech. Experiments were conducted on the Berlin emotional speech database for a three- class problem (anger, boredom and neutral emotional states). In order to evaluate the discrimination ability of the features three different classifiers were implemented: k-nearest neighbor, Bayesian Linear and quadratic. The highest accuracy results are obtained when neutral and anger emotions are evaluated.
{"title":"Automatic emotion detection in speech using mel frequency cesptral coefficients","authors":"S. Bedoya-Jaramillo, E. Belalcázar-Bolaños, T. Villa-Cañas, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla","doi":"10.1109/STSIVA.2012.6340558","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340558","url":null,"abstract":"Emotional states produce physiological alterations in the vocal tract introducing variability in the acoustic parameters of speech. Emotion recognition in speech can be used in human-machine interaction applications, speaker verification, analysis of neurological disorders and psychological diagnostic tools. This paper proposes the use of Mel Frequency Cesptral Coefficients (MFCC) for automatic detection of emotions in running speech. Experiments were conducted on the Berlin emotional speech database for a three- class problem (anger, boredom and neutral emotional states). In order to evaluate the discrimination ability of the features three different classifiers were implemented: k-nearest neighbor, Bayesian Linear and quadratic. The highest accuracy results are obtained when neutral and anger emotions are evaluated.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"10863 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116010789","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 : 2012-11-12DOI: 10.1109/STSIVA.2012.6340598
C. Isaza, J. Vargas, C. Gaviria, L. Hernández
In this article, a system that allows optical recognition of characters in the Colombian national identity card is presented. The system is shaped by an image acquisition algorithm, by running drivers over Windows, working together with a methodology that does OCR by eliminating of the holographic background that is the mean trouble in this problem. Performance of this methodology was measured through testing with a data base of 34 identity cards. A 92.6% of success in character recognition was obtained.
{"title":"Automatic OCR system for colombian DNIs","authors":"C. Isaza, J. Vargas, C. Gaviria, L. Hernández","doi":"10.1109/STSIVA.2012.6340598","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340598","url":null,"abstract":"In this article, a system that allows optical recognition of characters in the Colombian national identity card is presented. The system is shaped by an image acquisition algorithm, by running drivers over Windows, working together with a methodology that does OCR by eliminating of the holographic background that is the mean trouble in this problem. Performance of this methodology was measured through testing with a data base of 34 identity cards. A 92.6% of success in character recognition was obtained.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131564399","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 : 2012-11-12DOI: 10.1109/STSIVA.2012.6340595
C. E. Valderrama, G. Ulloa
This paper intends to be a literature review in the field of emotions detection using spectral analysis of neurological signals. It also shows the great boom in Brain Computer Interfaces (BCI) applications. Explains the research methodology used for this type of projects, and finally it highlights the results of several studies that have been done in this area.
{"title":"Spectral Analysis of physiological parameters for emotion detection","authors":"C. E. Valderrama, G. Ulloa","doi":"10.1109/STSIVA.2012.6340595","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340595","url":null,"abstract":"This paper intends to be a literature review in the field of emotions detection using spectral analysis of neurological signals. It also shows the great boom in Brain Computer Interfaces (BCI) applications. Explains the research methodology used for this type of projects, and finally it highlights the results of several studies that have been done in this area.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126851920","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 : 2012-09-01DOI: 10.1109/STSIVA.2012.6340587
Sebastian Agrado Castano, D. Guarín, Álvaro A. Orozco
In recent years the location of brain structures as the basal ganglia has shown to be a useful tool in surgery of patients suffering from neurodegenerative diseases like Parkinson's disease, where it is needed the implantation of a neurostimulator in the subthalamic nucleus (STN). Despite the different existing approaches that seek to address this problem, it is still possible to improve classification rates because during the stage of preprocessing of the signals from microelectrodes (which capture the neuronal activity of the brain), usually filtering a known signal portion: background neuronal activity. This preprocessing is done under the assumption that this part of the signal is not relevant for the classification process. However, in no event processing is performed to validate this assumption. This paper develops a methodology for the detection of determinism in background neuronal activity in the microelectrode recording signals (MER): application to Parkinson's disease. The proposal is based on the method of surrogate data, nonlinear tool has now been widely used for time series analysis, especially in physiological series.
{"title":"Detection of determinism in neuronal activity background from microelectrodes recording signals","authors":"Sebastian Agrado Castano, D. Guarín, Álvaro A. Orozco","doi":"10.1109/STSIVA.2012.6340587","DOIUrl":"https://doi.org/10.1109/STSIVA.2012.6340587","url":null,"abstract":"In recent years the location of brain structures as the basal ganglia has shown to be a useful tool in surgery of patients suffering from neurodegenerative diseases like Parkinson's disease, where it is needed the implantation of a neurostimulator in the subthalamic nucleus (STN). Despite the different existing approaches that seek to address this problem, it is still possible to improve classification rates because during the stage of preprocessing of the signals from microelectrodes (which capture the neuronal activity of the brain), usually filtering a known signal portion: background neuronal activity. This preprocessing is done under the assumption that this part of the signal is not relevant for the classification process. However, in no event processing is performed to validate this assumption. This paper develops a methodology for the detection of determinism in background neuronal activity in the microelectrode recording signals (MER): application to Parkinson's disease. The proposal is based on the method of surrogate data, nonlinear tool has now been widely used for time series analysis, especially in physiological series.","PeriodicalId":383297,"journal":{"name":"2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129689177","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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