International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)最新文献_第2页

Reflective code for gray block embedding 灰色块嵌入的反射代码

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208346

S. Janakiraman, N. Suriya, V. Nithiya, B. Radhakrishnan, J. Ramanathan, Rengarajan Amirtharajan

引用次数: 7

An improved support vector machine kernel for medical image retrieval system 一种改进的支持向量机核医学图像检索系统

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208354

M. S. Kumar, Y. S. Kumaraswamy

{"title":"An improved support vector machine kernel for medical image retrieval system","authors":"M. S. Kumar, Y. S. Kumaraswamy","doi":"10.1109/ICPRIME.2012.6208354","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208354","url":null,"abstract":"Digital medical images take up most of the storage space in the medical database. Digital images are in the form of X-Rays, MRI, CT. These medical images are extensively used in diagnosis and planning treatment schedule. Retrieving required medical images from the database in an efficient manner for diagnosis, research and educational purposes is essential. Image retrieval systems are used to retrieve similar images from database by inputting a query image. Image retrieval systems extract features in the image to a feature vector and use similarity measures for retrieval of images from the database. So the efficiency of the image retrieval system depends upon the feature selection and its classification. In this paper, it is proposed to implement a novel feature selection mechanism using Discrete Sine Transforms (DST) with Information Gain for feature reduction. Classification results obtained from existing Support Vector Machine (SVM) is compared with the proposed Support Vector Machine model. Results obtained show that the proposed SVM classifier outperforms conventional SVM classifier and multi layer perceptron neural network.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129161360","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: 7

Cauchy-Euler model, cellular automata simulation of the rate of recovery of the infected airway from COPD Cauchy-Euler模型，细胞自动机模拟COPD感染气道的恢复率

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208368

B. M. Vaganan, D. Pandiaraja, S. Sundar, E. E. Priya

引用次数: 2

Modified backpropagation algorithm with adaptive learning rate based on differential errors and differential functional constraints 基于微分误差和微分函数约束的自适应学习率改进反向传播算法

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208288

T. Kathirvalavakumar, S. J. Subavathi

引用次数: 4

Mammogram image segmentation using granular computing based on rough entropy 基于粗糙熵的乳房x线图像分割的颗粒计算

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208365

R. Roselin, K. Thangavel

引用次数: 7

Image segmentation using nearest neighbor classifiers based on kernel formation for medical images 基于核形成的医学图像最近邻分类器图像分割

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208355

R. Harini, C. Chandrasekar

引用次数: 10

Computational unfoldment of mammograms 乳房x线照片的计算展开

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208366

M. Joshi, A. Bhale

{"title":"Computational unfoldment of mammograms","authors":"M. Joshi, A. Bhale","doi":"10.1109/ICPRIME.2012.6208366","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208366","url":null,"abstract":"The importance of mammograms in early breast cancer detection is an accepted fact. Mammograms (either an analog x-ray film or a digital softcopy) are computationally empowered to extract significant information. Several computational techniques/algorithms process mammograms to highlight and reveal otherwise unseen features. Thus mammographic images are computationally unfolded to obtain appropriate information that can be used for further analysis. Computational analysis of mammograms is an essential tool, which is used by numerous specialists for various purposes. In this paper we review such research work reported in the literature in recent years. Our focus is in particular on computational preprocessing of mammograms. Preprocessing involves enhancement of mammographic images as well as extraction of relevant features from images. We grouped various image enhancement research approaches systematically. We also categorized various research techniques based on the types of features that are extracted and used to obtain intended results. Although mammograms are used mostly for breast cancer detection, the research is not confined to this aspect only. Several other areas that deal with mammograms are also explored by researchers including image compression, Content based Image Retrieval (CBIR) etc. Variety in these research applications is also discussed and presented in this paper.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221623","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: 2

A new approach to reduce flooding in Grid Fisheye state routing (GFSR) protocol by propagation neighborhood 基于传播邻域的网格鱼眼状态路由(GFSR)协议减少泛洪的新方法

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208341

S. Nithya, Rekha C Chandrasekar, R. Kaniezhil

{"title":"A new approach to reduce flooding in Grid Fisheye state routing (GFSR) protocol by propagation neighborhood","authors":"S. Nithya, Rekha C Chandrasekar, R. Kaniezhil","doi":"10.1109/ICPRIME.2012.6208341","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208341","url":null,"abstract":"Mobile Ad-hoc Network (MANET) is the self organizing collection of mobile nodes. Ad hoc wireless networks have massive commercial and military potential because of their mobility support. Quality of Service (QoS) routing in mobile Ad-Hoc networks is challenging due to rapid change in network topology. In this paper, we focused to reduce flooding performance of the Fisheye State Routing (FSR) protocol in Grid using ns-2 network simulator under different performance metrics scenario in respect to number of Nodes and Pause-Time. The connection establishment is costly in terms of time and resource where the network is mostly affected by connection request flooding. The proposed approach presents a way to reduce flooding in MANETs. Flooding is dictated by the propagation of connection-request packets from the source to its neighborhood nodes. The proposed architecture promotes on the concept of sharing neighborhood information. The proposed approach focuses on exposing its neighborhood peer to another node that is referred to as its friend-node, which had requested/forwarded connection request. If there is a high probability for the friend node to communicate through the exposed routes, this could improve the efficacy of bandwidth utilization by reducing flooding, as the routes have been acquired, without any broadcasts. Friendship between nodes is quantized based on empirical computations and heuristic algorithms. The nodes store the neighborhood information in their cache that is periodically verified for consistency. Simulation results show the performance of this proposed method.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116960098","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: 3

Geometric feature based face-sketch recognition 基于几何特征的人脸素描识别

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208381

S. Pramanik, D. Bhattacharjee

{"title":"Geometric feature based face-sketch recognition","authors":"S. Pramanik, D. Bhattacharjee","doi":"10.1109/ICPRIME.2012.6208381","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208381","url":null,"abstract":"This paper presents a novel facial sketch image or face-sketch recognition approach based on facial feature extraction. To recognize a face-sketch, we have concentrated on a set of geometric face features like eyes, nose, eyebrows, lips, etc and their length and width ratio because it is difficult to match photos and sketches because they belong to two different modalities. In this system, first the facial features/components from training images are extracted, then ratios of length, width, and area etc. are calculated and those are stored as feature vectors for individual images. After that the mean feature vectors are computed and subtracted from each feature vector for centering of the feature vectors. In the next phase, feature vector for the incoming probe face-sketch is also computed in similar fashion. Here, K-NN classifier is used to recognize probe face-sketch. It is experimentally verified that the proposed method is robust against faces are in a frontal pose, with normal lighting and neutral expression and have no occlusions. The experiment has been conducted with 80 male and female face images from different face databases. It has useful applications for both law enforcement and digital entertainment.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117029467","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: 34

Segregating unique service object from multi-web sources for effective visualization 从多个web源中分离出唯一的服务对象，以实现有效的可视化

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012) Pub Date : 2012-03-21 DOI: 10.1109/ICPRIME.2012.6208283

S. Jayanthi, S. Prema

{"title":"Segregating unique service object from multi-web sources for effective visualization","authors":"S. Jayanthi, S. Prema","doi":"10.1109/ICPRIME.2012.6208283","DOIUrl":"https://doi.org/10.1109/ICPRIME.2012.6208283","url":null,"abstract":"Web services describe a standardized way of integrating Web-based applications using the XML (Extensible Markup Language), SOAP (Simple Object Access Protocol), WSDL and UDDI (Universal Description Discovery and Integration) open standards over an Internet protocol backbone. WSDL (Web Service Definition Language) is used for describing the available services. The dynamic approach starts with crawling on the Web for Web Services, simultaneously gathering the WSDL service descriptions and related documents. The Web APIs provide the methodology for building unique service objects from multiple web resources. In this semantic search engine, if the web user gets satisfied with the description they can crawl into the webpage, otherwise they can shift to another link. This query enhancement process is exploited to learn useful information that helps to generate related queries. In this research work the add-on is automatically generated when compared with the existing system. Add-on is programs that are integrated into the browser application, usually providing additional functionality. Finally this work gives an overview of how to segregate the unique service object (USO) using Bookshelf Data Structure from web resources and use it to semantically annotate the resulting services in visual mode.","PeriodicalId":148511,"journal":{"name":"International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119007","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