2015 International Conference on Communications and Signal Processing (ICCSP)最新文献_第10页

Brain FMRI clustering using interaction K-means algorithm with PCA 基于交互K-means算法与PCA的脑FMRI聚类

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322628

K. Vijay, K. Selvakumar

{"title":"Brain FMRI clustering using interaction K-means algorithm with PCA","authors":"K. Vijay, K. Selvakumar","doi":"10.1109/ICCSP.2015.7322628","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322628","url":null,"abstract":"An uncontrolled development of tissues in the human being is a tumor. To spot exact locality of tumor and its data being an essential task. To find the tumor, magnetic resonance image has used. FMRI (Functional Magnetic Resonance Imaging) is non-invasive procedure is to see the brain activity and to calculate of blood circulation level in the brain. The FMRI data are time series of 3D-dimensional volume images of the brain based on interaction pattern. This data is traditionally analyzed within a mass-univariate framework essentially relying on classical inferential statistics. Segmentation of FMRI plays a vital role to acquire the data of brain activities of the human brain. Feature Selection is a complicated to handle in Interaction pattern. To overcome the difficulty of the feature selection process, we use the Principal Component Analysis (PCA). PCA is a technique to pre-process the data before carrying out any data mining responsibilities, e.g., categorization and grouping. By this PC Analysis, profitable predictors are achievable in FMRI data. Using the features selected from PCA, we present a clustering novel technique. Based on this new cluster notion interaction K-means (IKM) have applied. IKM is a well-organized procedure for clustering. In this paper, Trained MRI data has taken out using the PC Analysis and IKM technique have applied over the specified data. By this, improvement has conquered in the performance in terms of accuracy and complexity in multivariate data.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"13 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":"132670028","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}

引用次数: 16

Mechanical movement aid to nerve damaged and parkinson's using pressure & frequency detection (pseudo arm controller) 机械运动辅助神经损伤和帕金森氏症使用压力和频率检测(假手臂控制器)

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322775

Eram Khan, Ashish Panchal

{"title":"Mechanical movement aid to nerve damaged and parkinson's using pressure & frequency detection (pseudo arm controller)","authors":"Eram Khan, Ashish Panchal","doi":"10.1109/ICCSP.2015.7322775","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322775","url":null,"abstract":"This paper proposes a novel method of using external helping mechanism for increasing interactivity of human arm for paralytic patients. Restricting unwanted movements in a Parkinson's patient will also be possible. This external helping mechanism was constructed using pressure sensor for detection of minuet muscle pressure applied by the user. DC coreless motor to control the movement of metallic finger frame, which in turn are connected to the user's arm. Fast and reliable responses, low power consumption pseudo arm controller. MCU is used to acquisition and processing data of the piezoelectric pressure sensors. The device can be worn as a glove by the user. The second part of this arm is a claw designed to give mechanical restriction to the hand of a Parkinson's patients preventing unwanted movement. A MEMS accelerometer and a MEMS gyro in a single chip. The sensor uses I2C bus to interface with MCU. By activation of the claw if frequency of hand movement is above 1-2Hz it is possible to restrict unwanted movement.The frequency of a normal hand tremor is 9-25Hz, of an essential tremor is 4-12Hz and of a Parkinson's patient is 3-8Hz.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"58 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134092621","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}

引用次数: 0

Software based distributed shared memory (DSM) model using shared variables between multiprocessors 基于软件的分布式共享内存(DSM)模型，在多处理器之间使用共享变量

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322749

H. Vasava, J M Rathod

{"title":"Software based distributed shared memory (DSM) model using shared variables between multiprocessors","authors":"H. Vasava, J M Rathod","doi":"10.1109/ICCSP.2015.7322749","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322749","url":null,"abstract":"A Distributed shared memory systems represent a successful hybrid of two parallel computer classes: distributed computer systems and shared memory multiprocessors. They provide the shared memory abstraction in systems with physically distributed memories, and consequently combine the advantages of both approaches. Distributed shared memory is the abstraction that supports the shared memory in a physically non-shared (distributed) architecture. Shared memory is a simple yet powerful paradigm for structuring systems. Recently, there has been an interest in extending this paradigm to non-shared memory architectures as well. For example, the virtual address spaces for all variables in a distributed variable-based system could be viewed as constituting a global distributed shared memory. The Distributed shared memory system is designed on the basis of page-based, shared-variable-based or object-based access. There are certain advantages and disadvantages of each access methodology. We propose a shared variable based DSM model for managing distributed shared memory. These paper also present implementation levels with its several issues require to be consider. We have presented an implementation of this model in the context of a linux operating system.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"45 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":"130352213","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}

引用次数: 5

MUSIC and improved MUSIC algorithm to estimate direction of arrival MUSIC和改进的MUSIC算法估计到达方向

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322593

Pooja Gupta, S. P. Kar

{"title":"MUSIC and improved MUSIC algorithm to estimate direction of arrival","authors":"Pooja Gupta, S. P. Kar","doi":"10.1109/ICCSP.2015.7322593","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322593","url":null,"abstract":"The DOA estimation in array signal processing is one of the important and emerging research area. The effectiveness of this direction of arrival estimation greatly determines the performance of smart antennas. It works on the digitized output from each sensor array. The estimation results for coherent signals, broadband signals and multiple signals are of greater consideration. Various information of the parameters relating to a particular wave can be obtained by analyzing the incoming wave that is received by a sensor or an array of sensors. The accuracy in the estimation of direction of arrival is very crucial in array signal processing. DOA estimation has vital applications in radar, sonar, seismology, earthquake, astronomy, biomedicine and communication. This paper presents an overview of direction of arrival estimation using the MUSIC algorithm. This algorithm is a peak search method to estimate the arrival angle. The paper emphasizes on the factors that can affect the results of the estimation process and describes the concept of estimating the arrival angle. The MATLAB simulations shown here highlight the factors that can improve accuracy. The factors include the array element spacing, number of array elements, number of snapshots and the signal incidence angle difference. Attempts are made to bring about better resolution and contrast. As the conventional MUSIC algorithm is found to have less efficiency for coherent signals, better simulations using an improved MUSIC algorithm in provided in this paper.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"16 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":"124331820","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}

引用次数: 67

Feature extraction of Heterogeneous face images using SIFT and MLBP algorithm 基于SIFT和MLBP算法的异质人脸图像特征提取

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322716

K. Kalamkar, P. Mohod

{"title":"Feature extraction of Heterogeneous face images using SIFT and MLBP algorithm","authors":"K. Kalamkar, P. Mohod","doi":"10.1109/ICCSP.2015.7322716","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322716","url":null,"abstract":"Humans often use the faces to recognize and similar recognition can enable automatically now by advancement in computing capabilities. The recognition process has now been matured into a science of sophisticated mathematical representation and matching process than early face recognition have been used simple geometric models. Face recognition has received a great deal of attention over the last few years because of its many applications in various domains. The main objective is to extract the distinctive invariance features from the Heterogeneous images from different scenarios that can be use to perform reliable matching between probe and gallery images. The features are highly distinct, so that single feature can be correctly matched with high probability against a large database of features from many images. Previous approaches extracts features from only one type such as matching a face with a gallery but in this paper we are proposing an approach to match a face in different scenario such as near infrared (NIR), thermal photograph, viewed sketch and forensic sketch. Initially we remove the noise from the image. To remove the noise present in the image we use three filters- Gaussian, Difference of Gaussian, CSDN. Then to extract distinct features by using SIFT and MLBP.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"23 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":"125553081","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}

引用次数: 4

Evaluation of wavelet based ECG steganography system by using Percentage Residual Difference (PRD) measurements 基于残差百分比测量的心电隐写系统评价

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322548

Deepali Awasthi, S. Madhe

{"title":"Evaluation of wavelet based ECG steganography system by using Percentage Residual Difference (PRD) measurements","authors":"Deepali Awasthi, S. Madhe","doi":"10.1109/ICCSP.2015.7322548","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322548","url":null,"abstract":"Remote healthcare monitoring and Point of Care (PoC) based systems are widely used for managing diagnostic information of patients. These systems introduce many threats such as privacy, security data integrity, reliability, accuracy, etc. issues. In this paper, a new technique is introduced for solving the problem of privacy and security issues. In proposed method, ECG steganography technique using Discrete Wavelet Transforms (DWT) is implemented. This method is based on encryption and decryption techniques. Encryption method is used to hide the patient information inside the ECG signal by using scrambling matrix and shared key and produces the watermarked ECG signal. Decryption method is used to extract the patient secret information from the ECG signal by using same shared key and scrambling matrix. For evaluating the diagnosability, Percentage Residual Difference (PRD) and extracted PRD measurements are analyzed. From the results, table are calculated that there is no difference between PRD of original ECG and extracted ECG so watermarked ECG is also used for diagnosis purpose. In this paper, Signal to Noise Ratio (SNR) of normal PRD and extracted PRD are calculated using different wavelets and we have concluded that sym20 wavelet gives better response from the results than any other wavelet.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"139 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":"122128291","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}

引用次数: 5

Study the effect of music on HRV signal using 3D Poincare plot in spherical Co-ordinates - A signal processing approach 利用球面坐标系中的三维庞加莱图研究音乐对HRV信号的影响-一种信号处理方法

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322652

Madhuparna Das, Tuhin Jana, Parna Dutta, R. Banerjee, A. Dey, D. K. Bhattacharya, M. Kanjilal

{"title":"Study the effect of music on HRV signal using 3D Poincare plot in spherical Co-ordinates - A signal processing approach","authors":"Madhuparna Das, Tuhin Jana, Parna Dutta, R. Banerjee, A. Dey, D. K. Bhattacharya, M. Kanjilal","doi":"10.1109/ICCSP.2015.7322652","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322652","url":null,"abstract":"In this article, we study the effect of music on human body and mind. As a parameter for measurement of the physiological condition we choose the heart rate variability signals taken from subjects listening to a particular type of music, which is Rabindra Sangeet (love chapter) in our case. The subjects are allowed to listen to the music for a fixed time span and then we take easements of HRV signals with our own ECG machine. For data analysis the Poincaré plot in spherical coordinate is used. Each of the plots obtained from second order differences form a single cluster looking almost like an ellipse having some outliers. We observe that the volume of the cluster is reduced remarkably in the data of the on music state as compared to the data of pre music state; further the amount of reduction is not the same for all the subjects. This proves that music has some definite common effect on human physiology. Our study shows that this particular type of music gives a complete different physiology. This can possibly be used as a tool to deal with different medical problems such as stress management or hypertension.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"261 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":"123103346","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}

引用次数: 8

Survey on low power adaptive image compression techniques for WSN 无线传感器网络低功耗自适应图像压缩技术研究进展

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322679

H. Rekha, P. Samundiswary

引用次数: 4

Fast fractal image encoding scheme based on Absolute value of Pearson correlation coefficient 基于Pearson相关系数绝对值的快速分形图像编码方案

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322657

Priyanka Mendhe, Rupali S. Balpande, A. Khobragade

引用次数: 0

Content Based retinal Image Retrieval scheme using Harmony Search Algorithm 基于内容的和声搜索视网膜图像检索方案

2015 International Conference on Communications and Signal Processing (ICCSP) Pub Date : 2015-04-02 DOI: 10.1109/ICCSP.2015.7322559

J. Sivakamasundari, V. Natarajan

{"title":"Content Based retinal Image Retrieval scheme using Harmony Search Algorithm","authors":"J. Sivakamasundari, V. Natarajan","doi":"10.1109/ICCSP.2015.7322559","DOIUrl":"https://doi.org/10.1109/ICCSP.2015.7322559","url":null,"abstract":"Automated segmentation of vasculatures in retinal images is vital for the detection of Diabetic Retinopathy (DR). An attempt has been made to generate continuous vasculature information using evolutionary based Harmony Search Algorithm (HSA) combined with conventional Multilevel Thresholding (MLT) methods. The preprocessed normal and abnormal retinal images are segmented using HSA based Otsu and Kapur MLT methods by the best objective functions. The segmentation is validated with corresponding ground truth images using binary similarity measures. The statistical, textural and structural features are obtained from the segmented images and are analyzed. Content Based Image Retrieval (CBIR) is used to assist physicians in clinical diagnoses and research fields. The CBIR systems are developed based on both the MLT segmentation techniques and the obtained features. Similarity matching is carried out between the features of query and database images using the Euclidean Distance measure. Similar images are ranked and retrieved. This work shows high retrieval performances such as precision (96%) and recall (58%) for the CBIR system using HSA based Otsu MLT segmentation method than the other method. Hence this CBIR system could be recommended in computer assisted diagnosis for a better screening of the diabetic retinopathy.","PeriodicalId":174192,"journal":{"name":"2015 International Conference on Communications and Signal Processing (ICCSP)","volume":"27 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":"131754496","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}

引用次数: 1