Pub Date : 2017-09-01DOI: 10.1109/ISPCC.2017.8269719
R. Prajapati, V. Garg
In recent years, standalone systems are becoming economic and substantial for the electrification in remote areas, where grid connectivity is difficult. This paper presents an approach for electrification of shadow regions in Himalayan area, where the solar energy is not sufficient. The method presented uses the wind-diesel hybrid system for generation of electricity to meet the electric power requirements for a cluster of villages. The approach is novel as it uses small rotor wind turbines (SRWT) in the wind-diesel system. The advantages of using SRWT are (i) low cost, (ii) small in size, (iii) low-speed operation, and (iv) affordable for rural communities. The paper discusses the sizing of different system components to find out optimal combination of energy for the selected study while minimizing the cost of energy (COE) generation for required reliability values. The sizing is performed for three different seasonal load profiles. The two reliability values are considered for the selection of optimum solution of year round application. The proposed model provides continuous supply of electricity while minimizing the energy.
{"title":"Optimal sizing of standalone small rotor wind and diesel system with energy storage for low speed wind operation","authors":"R. Prajapati, V. Garg","doi":"10.1109/ISPCC.2017.8269719","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269719","url":null,"abstract":"In recent years, standalone systems are becoming economic and substantial for the electrification in remote areas, where grid connectivity is difficult. This paper presents an approach for electrification of shadow regions in Himalayan area, where the solar energy is not sufficient. The method presented uses the wind-diesel hybrid system for generation of electricity to meet the electric power requirements for a cluster of villages. The approach is novel as it uses small rotor wind turbines (SRWT) in the wind-diesel system. The advantages of using SRWT are (i) low cost, (ii) small in size, (iii) low-speed operation, and (iv) affordable for rural communities. The paper discusses the sizing of different system components to find out optimal combination of energy for the selected study while minimizing the cost of energy (COE) generation for required reliability values. The sizing is performed for three different seasonal load profiles. The two reliability values are considered for the selection of optimum solution of year round application. The proposed model provides continuous supply of electricity while minimizing the energy.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"19 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114038267","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269698
Rama Rani, Gaurav Deep
Steganography is a technique of concealing private information in a cover medium in such a way that it becomes impossible for the third person to come to know that some confidential information is contained in the cover envelope. In today's era with the inception of new emerging technologies, barcodes has become one of the most popular methods to provide a mechanism for protecting sensitive information.3D barcodes are used to accommodate high data rates by making use of third dimension as a color. 3D barcodes serves as the most reliable technique to hide data because they do not make use of any error correction levels due to the reason that it is very difficult to alter the encoded information. This paper introduces the concept of data hiding in barcodes by using color as third dimension. The process is classified into different categories and performance is evaluated by using various statistical parameters.
{"title":"Digital 3D barcode image as a container for data hiding using steganography","authors":"Rama Rani, Gaurav Deep","doi":"10.1109/ISPCC.2017.8269698","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269698","url":null,"abstract":"Steganography is a technique of concealing private information in a cover medium in such a way that it becomes impossible for the third person to come to know that some confidential information is contained in the cover envelope. In today's era with the inception of new emerging technologies, barcodes has become one of the most popular methods to provide a mechanism for protecting sensitive information.3D barcodes are used to accommodate high data rates by making use of third dimension as a color. 3D barcodes serves as the most reliable technique to hide data because they do not make use of any error correction levels due to the reason that it is very difficult to alter the encoded information. This paper introduces the concept of data hiding in barcodes by using color as third dimension. The process is classified into different categories and performance is evaluated by using various statistical parameters.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130902934","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269646
Ruchika Chawla, Prateek Thakral, Akshay Kumar Kaura, Kapil O. Gupta
Traffic control at intersection is a system where conflict resolution between different lanes is required so that vehicles can access the intersection without hitting each other and also which prevents deadlocks. With the emergence of Vehicular Ad Hoc Networks (VANETs), Intelligent Transportation Systems (ITS) has seen emergence of new algorithms for autonomous cars such as collision detection, traffic maneuver & traffic control at intersection. Traffic light based algorithms use complex computational mechanism such as neural network and machine learning which make these algorithms complex to implement and use. The approach which we are going to discuss in this paper is to model the problem as the Vehicle Mutual Exclusion for Intersections (VMEI) which provides centralized solution to this problem. In VMEI approach number of vehicles that can access the intersection in one pass is not at all defined and it is left to the human intervention, we will call it as threshold. In this paper we will provide solution to threshold problem in centralized approach.
{"title":"Modified centralized approach for preventing collision at traffic intersection","authors":"Ruchika Chawla, Prateek Thakral, Akshay Kumar Kaura, Kapil O. Gupta","doi":"10.1109/ISPCC.2017.8269646","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269646","url":null,"abstract":"Traffic control at intersection is a system where conflict resolution between different lanes is required so that vehicles can access the intersection without hitting each other and also which prevents deadlocks. With the emergence of Vehicular Ad Hoc Networks (VANETs), Intelligent Transportation Systems (ITS) has seen emergence of new algorithms for autonomous cars such as collision detection, traffic maneuver & traffic control at intersection. Traffic light based algorithms use complex computational mechanism such as neural network and machine learning which make these algorithms complex to implement and use. The approach which we are going to discuss in this paper is to model the problem as the Vehicle Mutual Exclusion for Intersections (VMEI) which provides centralized solution to this problem. In VMEI approach number of vehicles that can access the intersection in one pass is not at all defined and it is left to the human intervention, we will call it as threshold. In this paper we will provide solution to threshold problem in centralized approach.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128318047","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269688
Nithin Varma Malathkar, S. Soni
An efficient compression algorithm for the capsule endoscopy is described in this paper. This paper consists of a simplified YUV color space, which is developed by taking endoscopy images unique properties into consideration. This is built on RGB-sYUV color conversion, differential pulse code modulation (DPCM) and Golomb-Rice encoder. This DPCM doesn't need any extra buffer memory to store one row of images and Golomb-Rice (G-R) code is simple and easily hardware implemented. This algorithm is lossless and give a compression ratio (CR) of 68.1%. It gives better results than the standard lossless algorithm regarding complexity and compression ratio in capsule endoscopy applications.
{"title":"Low-cost color space based image compression algorithm for capsule endoscopy","authors":"Nithin Varma Malathkar, S. Soni","doi":"10.1109/ISPCC.2017.8269688","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269688","url":null,"abstract":"An efficient compression algorithm for the capsule endoscopy is described in this paper. This paper consists of a simplified YUV color space, which is developed by taking endoscopy images unique properties into consideration. This is built on RGB-sYUV color conversion, differential pulse code modulation (DPCM) and Golomb-Rice encoder. This DPCM doesn't need any extra buffer memory to store one row of images and Golomb-Rice (G-R) code is simple and easily hardware implemented. This algorithm is lossless and give a compression ratio (CR) of 68.1%. It gives better results than the standard lossless algorithm regarding complexity and compression ratio in capsule endoscopy applications.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127851535","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269648
Pawanjot Kaur, Harbinder Singh, Vinay Kumar
The considerable information from different images of same scene can be integrated into single image by using image fusion which is worthy for human visualization and computer vision and other image-processing tasks. In this paper, single resolution weighted average image fusion approach based on morphological operations is proposed. To select salient infrared targets details from infrared imagery and spatial detailed information from visible imagery, the morphological operation are applied on input images for weight map computation. By adopting the proposed method, spatial information is mostly preserved and infrared targets can be easily visualized in the resulting fused images. Experimental results are demonstrated to support the validity of morphological operations for weighted average based fusion of infrared image and visible image.
{"title":"Salient infrared target and visible image fusion based on morphological segmentation","authors":"Pawanjot Kaur, Harbinder Singh, Vinay Kumar","doi":"10.1109/ISPCC.2017.8269648","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269648","url":null,"abstract":"The considerable information from different images of same scene can be integrated into single image by using image fusion which is worthy for human visualization and computer vision and other image-processing tasks. In this paper, single resolution weighted average image fusion approach based on morphological operations is proposed. To select salient infrared targets details from infrared imagery and spatial detailed information from visible imagery, the morphological operation are applied on input images for weight map computation. By adopting the proposed method, spatial information is mostly preserved and infrared targets can be easily visualized in the resulting fused images. Experimental results are demonstrated to support the validity of morphological operations for weighted average based fusion of infrared image and visible image.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132704878","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269694
Rudrika Kalsotra, Sakshi Arora
Moving object detection is an active research area in the field of video processing and computer vision forming the base of many video analytic applications. The typical impediments in detection of moving objects including dynamic scenes, sudden illumination variations, complex background, effects of shadows, bootstrapping, video noise and camouflage receive the attention of researchers around the globe. This study proposes a morphological based approach for moving object detection. Morphological operations are combined with background subtraction technique and thresholding for experimental purpose. Furthermore, this paper outlines the methods of moving object detection and summarizes the recent research trends in this direction. The goal of this research is to explore the effects of morphological changes on the detection of moving objects. The preliminary results indicate that the proposed approach can generate accurate and complete moving object keeping the required details intact for meaningful object detection.
{"title":"Morphological based moving object detection with background subtraction method","authors":"Rudrika Kalsotra, Sakshi Arora","doi":"10.1109/ISPCC.2017.8269694","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269694","url":null,"abstract":"Moving object detection is an active research area in the field of video processing and computer vision forming the base of many video analytic applications. The typical impediments in detection of moving objects including dynamic scenes, sudden illumination variations, complex background, effects of shadows, bootstrapping, video noise and camouflage receive the attention of researchers around the globe. This study proposes a morphological based approach for moving object detection. Morphological operations are combined with background subtraction technique and thresholding for experimental purpose. Furthermore, this paper outlines the methods of moving object detection and summarizes the recent research trends in this direction. The goal of this research is to explore the effects of morphological changes on the detection of moving objects. The preliminary results indicate that the proposed approach can generate accurate and complete moving object keeping the required details intact for meaningful object detection.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129330027","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269683
Ashutosh Sharma, Mohd Dilshad Ansari, Rajiv Kumar
Edge detection is one of the most fundamental operations in image processing and is one of the most commonly used operations in image processing and pattern recognition. The reason for this is that edges form the outline of an object and thus reduce the size of file without losing the useful information. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. Edge detection reduces the amount of data needed to process by removing unnecessary features. Knowing the positions of these boundaries is critical in the process of image enhancement, recognition, restoration and compression. The edges of image are considered to be most important image attributes that provide valuable information for human image perception. The areas of this work are in digital image process and telecommunication engineering, which are very wide fields. In this paper a comparison of different edge detectors has been made and results formed using the values of mean square error and peak signal to noise ratio shows that intuitionistic fuzzy edge detector outperform over the existed edge detectors.
{"title":"A comparative study of edge detectors in digital image processing","authors":"Ashutosh Sharma, Mohd Dilshad Ansari, Rajiv Kumar","doi":"10.1109/ISPCC.2017.8269683","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269683","url":null,"abstract":"Edge detection is one of the most fundamental operations in image processing and is one of the most commonly used operations in image processing and pattern recognition. The reason for this is that edges form the outline of an object and thus reduce the size of file without losing the useful information. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. Edge detection reduces the amount of data needed to process by removing unnecessary features. Knowing the positions of these boundaries is critical in the process of image enhancement, recognition, restoration and compression. The edges of image are considered to be most important image attributes that provide valuable information for human image perception. The areas of this work are in digital image process and telecommunication engineering, which are very wide fields. In this paper a comparison of different edge detectors has been made and results formed using the values of mean square error and peak signal to noise ratio shows that intuitionistic fuzzy edge detector outperform over the existed edge detectors.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117085349","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269676
Jyotindra Narayan, A. Singla
Robot kinematics plays a crucial role in recent advancements within industrial sectors and numerous medical applications. Finding forward kinematics, using DH convention is an easy task. As compared to forward kinematics, finding the inverse kinematics solution is far more challenging problem, especially when degrees-of-freedom (DOFs) are more. That is why; there is no general solution to the inverse kinematic problem of a given serial manipulator. This led to the development of alternate technique like fuzzy inference system (FIS) and neural network approach (NNA). This paper uses the combination of above two techniques, called as adaptive neuro fuzzy inference system (ANFIS), along with Gaussian membership function, in order to address the kinematic analysis of a 4-DOFs SCARA robot. The inverse kinematic solutions obtained using ANFIS are further utilized for desired path generation by the SCARA robot. Further, the complete analytical solution is developed in MATLAB environment for the validation purpose. It has been demonstrated with simulation runs that ANFIS results are satisfactory and are found in close approximation with analytical solutions.
{"title":"ANFIS based kinematic analysis of a 4-DOFs SCARA robot","authors":"Jyotindra Narayan, A. Singla","doi":"10.1109/ISPCC.2017.8269676","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269676","url":null,"abstract":"Robot kinematics plays a crucial role in recent advancements within industrial sectors and numerous medical applications. Finding forward kinematics, using DH convention is an easy task. As compared to forward kinematics, finding the inverse kinematics solution is far more challenging problem, especially when degrees-of-freedom (DOFs) are more. That is why; there is no general solution to the inverse kinematic problem of a given serial manipulator. This led to the development of alternate technique like fuzzy inference system (FIS) and neural network approach (NNA). This paper uses the combination of above two techniques, called as adaptive neuro fuzzy inference system (ANFIS), along with Gaussian membership function, in order to address the kinematic analysis of a 4-DOFs SCARA robot. The inverse kinematic solutions obtained using ANFIS are further utilized for desired path generation by the SCARA robot. Further, the complete analytical solution is developed in MATLAB environment for the validation purpose. It has been demonstrated with simulation runs that ANFIS results are satisfactory and are found in close approximation with analytical solutions.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127695522","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269751
P. Misra, A. Chintanpalli
A signal processing model based on temporal cues of auditory-nerve fibers had been developed to understand the level dependent changes in vowel identification scores. To this study, the rate-place cues of auditory-nerve fibers were added to the existing temporal model of vowel identification. The model includes the human version of the auditory-nerve model, with added rate-place cues, along with the neural network to identify vowels. The model predictions of vowel identification across levels with only temporal cues are compared with the model predictions with both temporal and rate-place cues of auditory-nerve fibers. This paper also analyses the vowel identification scores from the perspective of auditory-nerves corresponding to first and second formants (F1 and F2) besides the entire spectrum of auditory-nerve fibers. The model prediction revealed that the representation of second formant (F2) was improved with added rate-place cues especially at low-to-mid levels and could be associated with lower acoustic energy of F2. Thus, this paper possibly explains the role of rate-places cues for vowel identification scores across levels.
{"title":"Computational model predictions of level dependent changes in vowel identification with addition of rate-place cue","authors":"P. Misra, A. Chintanpalli","doi":"10.1109/ISPCC.2017.8269751","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269751","url":null,"abstract":"A signal processing model based on temporal cues of auditory-nerve fibers had been developed to understand the level dependent changes in vowel identification scores. To this study, the rate-place cues of auditory-nerve fibers were added to the existing temporal model of vowel identification. The model includes the human version of the auditory-nerve model, with added rate-place cues, along with the neural network to identify vowels. The model predictions of vowel identification across levels with only temporal cues are compared with the model predictions with both temporal and rate-place cues of auditory-nerve fibers. This paper also analyses the vowel identification scores from the perspective of auditory-nerves corresponding to first and second formants (F1 and F2) besides the entire spectrum of auditory-nerve fibers. The model prediction revealed that the representation of second formant (F2) was improved with added rate-place cues especially at low-to-mid levels and could be associated with lower acoustic energy of F2. Thus, this paper possibly explains the role of rate-places cues for vowel identification scores across levels.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":" 33","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132095860","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 : 2017-09-01DOI: 10.1109/ISPCC.2017.8269748
J. Kaur
Content-based image retrieval is a system which extracts the relevant set of images and matches with query image from large number of dataset. CBIR is used in many important areas such as education, defense, biomedical, crime prevention etc. In CBIR, the images are indexed according to content of image i.e. color, texture and shape that are derived from images. Many features and algorithms can be used to improve retrieval accuracy and to reduce the retrieval time. In this paper, we compare the different algorithms to extract color and texture features of an image and retrieve the relevant images. We measure the similarity between two images using different distance measures. The performance of each method has been individually evaluated in terms of average precision.
{"title":"Comparative analysis of color and texture features in content based image retrieval","authors":"J. Kaur","doi":"10.1109/ISPCC.2017.8269748","DOIUrl":"https://doi.org/10.1109/ISPCC.2017.8269748","url":null,"abstract":"Content-based image retrieval is a system which extracts the relevant set of images and matches with query image from large number of dataset. CBIR is used in many important areas such as education, defense, biomedical, crime prevention etc. In CBIR, the images are indexed according to content of image i.e. color, texture and shape that are derived from images. Many features and algorithms can be used to improve retrieval accuracy and to reduce the retrieval time. In this paper, we compare the different algorithms to extract color and texture features of an image and retrieve the relevant images. We measure the similarity between two images using different distance measures. The performance of each method has been individually evaluated in terms of average precision.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130832732","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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