2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering最新文献

Clustering centroid finding algorithm (CCFA) using spatial temporal data mining concept 基于时空数据挖掘概念的聚类质心查找算法

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496443

S. Baboo, K. Tajudin

引用次数: 6

A performance analysis and comparison of various routing protocols in MANET MANET中各种路由协议的性能分析与比较

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496508

M. Shobana, S. Karthik

引用次数: 19

Recognition of Arabic numerals with grouping and ungrouping using back propagation neural network 基于反向传播神经网络的阿拉伯数字分组与解组识别

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496494

P. Selvi, Selvikrish. selvi

{"title":"Recognition of Arabic numerals with grouping and ungrouping using back propagation neural network","authors":"P. Selvi, Selvikrish. selvi","doi":"10.1109/ICPRIME.2013.6496494","DOIUrl":"https://doi.org/10.1109/ICPRIME.2013.6496494","url":null,"abstract":"In this paper, the authors propose a method to recognize Arabic numerals using back propagation neural network. Arabic numerals are the ten digits that were descended from the Indian numeral system. Although the pattern of 0-9 is the same as in Indian numeral system, the glyphs vary for each numeral. The proposed method includes preprocessing of digitized handwritten image, training of BPNN and recognition phases. As a first step, the number of digits to be recognized is selected. The selected numerals are preprocessed for removal of noise and binarization. Separation process separates the numerals. Labelling, segmentation and normalization operations are performed for each of the separated numerals. The recognition phase recognizes the numerals accurately. The proposed method is implemented with Matlab coding. Sample handwritten images are tested with the proposed method and the results are plotted. With this method, the training performance rate was 99.4%. The accuracy value is calculated based on receiver operating characteristics and the confusion matrix. The value is calculated for each node in the network. The final result shows that the proposed method provides an recognition accuracy of more than 96%.","PeriodicalId":123210,"journal":{"name":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115056640","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: 14

Binary plane technique for super resolution image reconstruction using integer wavelet transform 基于整数小波变换的二值平面超分辨率图像重建技术

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496479

P. Babu, K. Prasad

引用次数: 1

Outdoor scene image segmentgation using statistical region merging 基于统计区域合并的室外场景图像分割

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496499

A. N. Kumar, C. Jothilakshmi, M. Ilamathi, S. Kalaiselvi

{"title":"Outdoor scene image segmentgation using statistical region merging","authors":"A. N. Kumar, C. Jothilakshmi, M. Ilamathi, S. Kalaiselvi","doi":"10.1109/ICPRIME.2013.6496499","DOIUrl":"https://doi.org/10.1109/ICPRIME.2013.6496499","url":null,"abstract":"A new loom of outdoor scene image segmentation algorithm is based on the region amalgamation. Here we are going to identify both structured (e.g. buildings, persons, car, etc.) and unstructured background objects (sky, road, grass, etc.) which are containing the some characteristic based on color, intensity, and texture in sequence. Our main aim is to solve the over segmented objects and strong reflection of objects. These problems are solved by using SRM (Statistical Region Merging) algorithm. In pre-processing the input image is converted into CIE (Commission Internationalde Eclairage) color space technique. Then bottom-up segmentation process is used to capture the structured and unstructured image characteristics. Another process is the Ada boost classifier which is used to classify the background objects in outdoor environment scenes. Ada boost is focused on difficult patterns. Then the contour maps are used to detect the boundary energy. Boundary detection test is the grouping of objects with a pair of connected neighboring regions. In this paper we have used an experimental result of two databases (Gould data set and Berkeley segmentation data set) and provide accurate segmentation using region merging. Finally the statistical region merging provides the groupings of images to identify the computer vision.","PeriodicalId":123210,"journal":{"name":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125621654","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

Packet size based performance analysis of IEEE 802.11 WLAN comprising virtual server arrays 基于分组大小的包含虚拟服务器阵列的IEEE 802.11 WLAN性能分析

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496445

Dr. V. Karthikeyani, Mr. T. Thiruvenkadam

引用次数: 3

A robust QR-Code video watermarking scheme based on SVD and DWT composite domain 基于SVD和DWT复合域的鲁棒qr码视频水印方案

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496482

G. Prabakaran, R. Bhavani, M. Ramesh

{"title":"A robust QR-Code video watermarking scheme based on SVD and DWT composite domain","authors":"G. Prabakaran, R. Bhavani, M. Ramesh","doi":"10.1109/ICPRIME.2013.6496482","DOIUrl":"https://doi.org/10.1109/ICPRIME.2013.6496482","url":null,"abstract":"Nowadays, Digital video is one of the popular multimedia data exchanged in the internet. Commercial activity on the internet and media require protection to enhance security. The 2D Barcode with a digital watermark is a widely interesting research in the security field. In this paper propose a video watermarking with text data (verification message) by using the Quick Response (QR) Code technique. The QR Code is prepared to be watermarked via a robust video watermarking scheme based on the (singular value decomposition)SVD and (Discrete Wavelet Transform)DWT. In addition to that logo (or) watermark gives the authorized ownership of video document. SVD is an attractive algebraic transform for watermarking applications. SVD is applied to the cover I-frame. The extracted diagonal value is fused with logo (or) watermark. DWT is applied on SVD cover image and QR code image. The inverse transform on watermarked image and add the frame into video this watermarked (include logo and QR code image) the video file sends to authorized customers. In the reverse process check the logo and QR code for authorized ownership. These experimental results can achieved acceptable imperceptibility and certain robustness in video processing.","PeriodicalId":123210,"journal":{"name":"2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133699090","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: 35

A survey on Iris Segmentation methods 虹膜分割方法综述

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496513

S. Jayalakshmi, M. Sundaresan

引用次数: 9

A predominant statistical approach to identify semantic similarity of textual documents 识别文本文档语义相似度的主要统计方法

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496721

P. Vigneshvaran, E. Jayabalan, K. Vijaya

引用次数: 2

Real time data acquisition system with self adaptive sampling rate using GPU 基于GPU的自适应采样率实时数据采集系统

2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering Pub Date : 2013-04-15 DOI: 10.1109/ICPRIME.2013.6496460

J. Thomas, C. Rajasekaran

引用次数: 0