Pub Date : 2015-04-02DOI: 10.1109/ICCSP.2015.7322687
Vaishnavi L. Kaundanya, A. Patil, A. Panat
This paper describes the performance of k-NN classifier to classify the different emotions. The human brain is a superimposition of the diverse processes. This complex structure of brain is recognized through EEG signals. EEG signals indicate the changes in the state of brain. Electroencephalograph (EEG) measurements are commonly used in different research areas under the field of medical. Data acquisition is done for different emotions with the help of ADInsruments' power lab instrument. The real life EEG signals are collected with the help of Ground Truth Method. In this paper, proposed method consists of four steps, viz., acquisition of data, Pre-processing, Feature extraction and Classification. Subjects are stimulated for Sad and Happy emotions. Statistical features are then given to a k-NN classifier. The k Nearest Neighbor classifier gives different accuracy of classification for different combinations of training and testing dataset. The system has been tested on number of subjects to observe the performance of k-NN classifier.
{"title":"Performance of k-NN classifier for emotion detection using EEG signals","authors":"Vaishnavi L. Kaundanya, A. Patil, A. Panat","doi":"10.1109/ICCSP.2015.7322687","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322687","url":null,"abstract":"This paper describes the performance of k-NN classifier to classify the different emotions. The human brain is a superimposition of the diverse processes. This complex structure of brain is recognized through EEG signals. EEG signals indicate the changes in the state of brain. Electroencephalograph (EEG) measurements are commonly used in different research areas under the field of medical. Data acquisition is done for different emotions with the help of ADInsruments' power lab instrument. The real life EEG signals are collected with the help of Ground Truth Method. In this paper, proposed method consists of four steps, viz., acquisition of data, Pre-processing, Feature extraction and Classification. Subjects are stimulated for Sad and Happy emotions. Statistical features are then given to a k-NN classifier. The k Nearest Neighbor classifier gives different accuracy of classification for different combinations of training and testing dataset. The system has been tested on number of subjects to observe the performance of k-NN classifier.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115895327","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322556
V. Chebolu, Siddharth Deshmukh
In this paper we propose an optimized multi-cell downlink beamforming solution in which our objective is to maximize capacity of a cellular network. We first formulate an optimization problem, maximizing the received signal power of every active user in a cell, subjected to limiting the overall interference observed by other users below a specified level. In addition, we also put constraint on maximum transmit power of the serving base station. Next, in order to compute robust beamforming vector we accommodate channel estimation error in our formulation. We consider channel imperfection as error between true and estimated channel coefficients and we assume error is bounded with in an ellipsoidal set. The resulting formulation is a non-convex optimization problem and to get a tractable solution we exploit linear matrix inequality based S-procedure. The final reformulation is solved by using semi definite relaxation. The efficacy of proposed solution in improving cellular capacity and efficient power transmission is shown by simulations.
{"title":"Cellular capacity maximization via robust downlink beamforming","authors":"V. Chebolu, Siddharth Deshmukh","doi":"10.1109/ICCSP.2015.7322556","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322556","url":null,"abstract":"In this paper we propose an optimized multi-cell downlink beamforming solution in which our objective is to maximize capacity of a cellular network. We first formulate an optimization problem, maximizing the received signal power of every active user in a cell, subjected to limiting the overall interference observed by other users below a specified level. In addition, we also put constraint on maximum transmit power of the serving base station. Next, in order to compute robust beamforming vector we accommodate channel estimation error in our formulation. We consider channel imperfection as error between true and estimated channel coefficients and we assume error is bounded with in an ellipsoidal set. The resulting formulation is a non-convex optimization problem and to get a tractable solution we exploit linear matrix inequality based S-procedure. The final reformulation is solved by using semi definite relaxation. The efficacy of proposed solution in improving cellular capacity and efficient power transmission is shown by simulations.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115919589","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322695
Nataraj A. Vijapur, Dr. R. Srinivasa Rao Kunte
Glaucoma is the most common cause of vision loss and is apparently becoming more important. In this paper, the research is focused on development of novel automated classification system for Glaucoma, based on image features from eye fundus photographs. A study done already has revealed that the optic cup-to-disc ratio, Neuro-retinal rim thickness and Neuro-retinal rim area in eye fundus image are the key parameters used to assess the progression of the disease. These aspects have been used by us for the detection of possible Glaucoma. Pearson-R coefficients corresponding to the eye fundus image are used as features. Segmentation algorithm is used to segment optic cup and disc and their respective vertical diameters are calculated to determine cup-to-disc ratio. Neuro-retinal rim thickness and rim area are measured using segmented portions of optic cup and disc. Methodology developed is found out to be very accurate for classification of Glaucoma. These novel techniques resulted in an overall efficiency of 97%.
{"title":"Glaucoma detection by using Pearson-R correlation filter","authors":"Nataraj A. Vijapur, Dr. R. Srinivasa Rao Kunte","doi":"10.1109/ICCSP.2015.7322695","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322695","url":null,"abstract":"Glaucoma is the most common cause of vision loss and is apparently becoming more important. In this paper, the research is focused on development of novel automated classification system for Glaucoma, based on image features from eye fundus photographs. A study done already has revealed that the optic cup-to-disc ratio, Neuro-retinal rim thickness and Neuro-retinal rim area in eye fundus image are the key parameters used to assess the progression of the disease. These aspects have been used by us for the detection of possible Glaucoma. Pearson-R coefficients corresponding to the eye fundus image are used as features. Segmentation algorithm is used to segment optic cup and disc and their respective vertical diameters are calculated to determine cup-to-disc ratio. Neuro-retinal rim thickness and rim area are measured using segmented portions of optic cup and disc. Methodology developed is found out to be very accurate for classification of Glaucoma. These novel techniques resulted in an overall efficiency of 97%.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124296541","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322845
M. Malkauthekar
Minutiae points are the most commonly used as well as accurate feature extraction method of fingerprint recognition system. Using biometrics for person identification is a growing field in many areas, which requires storage of database called template. Biometric system is vulnerable to attack. To reduce this drawback, cryptosystem is combined with biometric. Most common cryptosystem for fingerprint recognition system is fuzzy vault. In this work, two variable polynomial is used to conceal minutiae points, and only encoding is used to decide match/non match result. It gives same result as method which uses encoding and decoding of templates. It reduces computational complexity.
{"title":"Template security for fingerprint recognition system with two variables polynomial of fuzzy vault for minutiae points","authors":"M. Malkauthekar","doi":"10.1109/ICCSP.2015.7322845","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322845","url":null,"abstract":"Minutiae points are the most commonly used as well as accurate feature extraction method of fingerprint recognition system. Using biometrics for person identification is a growing field in many areas, which requires storage of database called template. Biometric system is vulnerable to attack. To reduce this drawback, cryptosystem is combined with biometric. Most common cryptosystem for fingerprint recognition system is fuzzy vault. In this work, two variable polynomial is used to conceal minutiae points, and only encoding is used to decide match/non match result. It gives same result as method which uses encoding and decoding of templates. It reduces computational complexity.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"345 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124312611","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322912
D. Singh
As there are new developments and innovation in the field of computer technology, size of electronic devices is decreasing rapidly. Thus, there is a need of new input interface for such devices. Increasingly we are recognizing the importance of human computing interaction (HCI) and in particular vision-based gesture and object recognition. Simple interfaces already exist, such as embedded keyboard, folder-keyboard and mini-keyboard. However, these interfaces need some amount of space to use and cannot be used while moving. Touch screens are a good control interface nowadays and are globally used in many applications. By applying vision technology and controlling the devices by natural hand gestures, we can reduce the work space required. In this paper, we propose a novel approach that uses a video device to control the Laptop using gestures.
{"title":"Recognizing hand gestures for human computer interaction","authors":"D. Singh","doi":"10.1109/ICCSP.2015.7322912","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322912","url":null,"abstract":"As there are new developments and innovation in the field of computer technology, size of electronic devices is decreasing rapidly. Thus, there is a need of new input interface for such devices. Increasingly we are recognizing the importance of human computing interaction (HCI) and in particular vision-based gesture and object recognition. Simple interfaces already exist, such as embedded keyboard, folder-keyboard and mini-keyboard. However, these interfaces need some amount of space to use and cannot be used while moving. Touch screens are a good control interface nowadays and are globally used in many applications. By applying vision technology and controlling the devices by natural hand gestures, we can reduce the work space required. In this paper, we propose a novel approach that uses a video device to control the Laptop using gestures.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124449233","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322864
Bineeth Kuriakose, J. Mathew, Balaji Balasubramaniam, K. P. Preena
Image - in today's digital world represented by numerical numbers. These numbers collectively present abstract concepts that is only understood by human perception. In this paper, we propose a novel framework that is more close to human perception of reality to translate the conventional representation of an image. Also, we focus on automating the image representation in terms of a natural language description both understandable by human and machine. The proposed framework can be extended to use a wide variety of real world applications in future.
{"title":"Deconstructing image semantics in natural language representation","authors":"Bineeth Kuriakose, J. Mathew, Balaji Balasubramaniam, K. P. Preena","doi":"10.1109/ICCSP.2015.7322864","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322864","url":null,"abstract":"Image - in today's digital world represented by numerical numbers. These numbers collectively present abstract concepts that is only understood by human perception. In this paper, we propose a novel framework that is more close to human perception of reality to translate the conventional representation of an image. Also, we focus on automating the image representation in terms of a natural language description both understandable by human and machine. The proposed framework can be extended to use a wide variety of real world applications in future.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114833199","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322768
P Pedda Sadhu Naik, T. Gopal
Segmentation is a process of partitioning the image into several objects. It plays a vital role in many fields such as satellite, remote sensing, object identification, face tracking and most importantly medical applications. Here in this paper, we here supposed to propose a novel image segmentation using iterative partitioning mean shift clustering algorithm, which overcomes the drawbacks of conventional clustering algorithms and provides a good segmented images. Simulation performance shows that the proposed scheme has performed superior to the existing clustering methods.
{"title":"A novel approach for color image segmentation using iterative partitioning mean shift clustering algorithm","authors":"P Pedda Sadhu Naik, T. Gopal","doi":"10.1109/ICCSP.2015.7322768","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322768","url":null,"abstract":"Segmentation is a process of partitioning the image into several objects. It plays a vital role in many fields such as satellite, remote sensing, object identification, face tracking and most importantly medical applications. Here in this paper, we here supposed to propose a novel image segmentation using iterative partitioning mean shift clustering algorithm, which overcomes the drawbacks of conventional clustering algorithms and provides a good segmented images. Simulation performance shows that the proposed scheme has performed superior to the existing clustering methods.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123562100","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322918
Pranaw Kumar, Avdhseh Kumar, Prapti Bhardwaj
We have investigated a unique design of microstrip antenna with dual band. The designed antenna constitutes of two C-shaped slots on patch. The C-shaped slots are arranged such that they form the mirror image of each other. The spacing between the two slots is chosen of 0.1cm. The proposed design reports a dual band with resonating frequency lying in ultra wideband region. The optimum gain reported for designed antenna is 6.1869dB. The return loss observed for antenna is -24.0982dB. Besides we have investigated VSWR which reports to be 1.0852.
{"title":"Design of double C-shaped microstrip antenna for application in UWB region","authors":"Pranaw Kumar, Avdhseh Kumar, Prapti Bhardwaj","doi":"10.1109/ICCSP.2015.7322918","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322918","url":null,"abstract":"We have investigated a unique design of microstrip antenna with dual band. The designed antenna constitutes of two C-shaped slots on patch. The C-shaped slots are arranged such that they form the mirror image of each other. The spacing between the two slots is chosen of 0.1cm. The proposed design reports a dual band with resonating frequency lying in ultra wideband region. The optimum gain reported for designed antenna is 6.1869dB. The return loss observed for antenna is -24.0982dB. Besides we have investigated VSWR which reports to be 1.0852.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122143521","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 : 2015-04-02DOI: 10.1109/ICCSP.2015.7322639
S. Lekha, M. Suchetha
Diabetes is a major problem affecting millions of people today and if left unchecked can create enormous implication on the health of the population. Among the various non invasive methods of detection, breath analysis presents an easier, more accurate and viable method in providing comprehensive clinical care for the disease. This paper examines the concentration of acetone levels in breath for monitoring blood glucose levels and thus predicting diabetes. The analysis uses the support vector mechanism to classify the response to healthy and diabetic samples. For the analysis ten subject samples of acetone levels are taken into consideration and are classified according to three labels which are healthy, type 1 diabetic and type 2 diabetic.
{"title":"Non- invasive diabetes detection and classification using breath analysis","authors":"S. Lekha, M. Suchetha","doi":"10.1109/ICCSP.2015.7322639","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322639","url":null,"abstract":"Diabetes is a major problem affecting millions of people today and if left unchecked can create enormous implication on the health of the population. Among the various non invasive methods of detection, breath analysis presents an easier, more accurate and viable method in providing comprehensive clinical care for the disease. This paper examines the concentration of acetone levels in breath for monitoring blood glucose levels and thus predicting diabetes. The analysis uses the support vector mechanism to classify the response to healthy and diabetic samples. For the analysis ten subject samples of acetone levels are taken into consideration and are classified according to three labels which are healthy, type 1 diabetic and type 2 diabetic.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123996233","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}
In this modern era of technology wireless sensor networks have broad area of applications. Various applications of sensor network needs the communication to be authenticated and secured. Researchers have developed many schemes for intruder detection in WSNs, but those schemes are very complicated and require complex encryption and decryption process for intruder detection. In this paper we proposed a intruder detection scheme based on (1, n) visual cryptography in which we use secure image which is partitioned into master share and ownership shares for verifying the authentication of sensor nodes. We believe that proposed technique will take fewer amounts of time and energy for intruder detection and possibly will detect all intruders in wireless sensor network. Main purpose of this paper is to introduce the use of visual cryptography in WSNs.
{"title":"Intruder detection by visual cryptography in wireless sensor networks","authors":"Jitendra Singh, Rakesh Kumar, Vimal Kumar, Ajai Mishra","doi":"10.1109/ICCSP.2015.7322745","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322745","url":null,"abstract":"In this modern era of technology wireless sensor networks have broad area of applications. Various applications of sensor network needs the communication to be authenticated and secured. Researchers have developed many schemes for intruder detection in WSNs, but those schemes are very complicated and require complex encryption and decryption process for intruder detection. In this paper we proposed a intruder detection scheme based on (1, n) visual cryptography in which we use secure image which is partitioned into master share and ownership shares for verifying the authentication of sensor nodes. We believe that proposed technique will take fewer amounts of time and energy for intruder detection and possibly will detect all intruders in wireless sensor network. Main purpose of this paper is to introduce the use of visual cryptography in WSNs.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128231547","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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