2010 IEEE 2nd International Advance Computing Conference (IACC)最新文献_第2页

Evolutionary approach for approximation of artificial neural network 人工神经网络逼近的进化方法

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423015

S. Pal, Swati Vipsita, P. Patra

引用次数: 3

An efficient decentralized Load Balancing Algorithm for grid 一种高效的网格分散负载均衡算法

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423048

P. K. Suri, Manpreet Singh

引用次数: 39

Script identification in a handwritten document image using texture features 使用纹理特征在手写文档图像中识别脚本

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423028

P. Hiremath, J. Pujari, S. Shivashankar, V. Mouneswara

引用次数: 37

DCT based texture watermarking using GLCM 基于DCT的GLCM纹理水印

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423014

S. Kamble, S. Agarwal, V. Shrivastava, Vikas Maheshkar

引用次数: 7

Detection and segmentation of lines and words in Gurmukhi handwritten text 古穆克语手写文本的行字检测与分词

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5422927

Rajiv Kumar, Amardeep Singh

{"title":"Detection and segmentation of lines and words in Gurmukhi handwritten text","authors":"Rajiv Kumar, Amardeep Singh","doi":"10.1109/IADCC.2010.5422927","DOIUrl":"https://doi.org/10.1109/IADCC.2010.5422927","url":null,"abstract":"The scanned text image is a non editable image though it has the text but one can not edit it or make any change, if required, to that scanned document. This provides a basis for the optical character recognition (OCR) theory. OCR is the process of recognizing a segmented part of the scanned image as a character. The overall OCR process consists of three major sub processes like pre processing, segmentation and then recognition. Out of these three, the segmentation process is the back bone of the overall OCR process. We can say that the segmentation process is the most significant process because if the segmentation is incorrect then we can not have the correct results; it is just like garbage in and garbage out. But it is not an easy job, because segmentation is one of the complex processes. It is more difficult if the document is handwritten because in that case only few points are there which can be used to make segmentation. In this paper, we formulate an approach to segment the scanned document image. As per this approach, initially this considers the whole image as one large window. Then this large window is broken into less large windows giving lines, once the lines are identified then each window consisting of a line is used to find a word present in that line and finally to characters. For that purpose we used the concept of variable sized window, that is, the window whose size can be adjusted according to needs. This concept was implemented and results were analyzed. After the analysis the same concept was modified and finally tried on different documents and we got good reasonable results.","PeriodicalId":249763,"journal":{"name":"2010 IEEE 2nd International Advance Computing Conference (IACC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122971595","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

Modifications in Genetic Algorithm using additional parameters to make them computationally efficient 使用附加参数对遗传算法进行修改，使其计算效率更高

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423037

B. Sridharan

引用次数: 7

Signature replacement attack and its counter-measures 签名替换攻击及其应对策略

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423006

Subrata Sinha, S. Sinha

引用次数: 4

An advanced secure (t, n) threshold proxy signature scheme based on RSA cryptosystem for known signers 针对已知签名者，提出了一种基于RSA密码系统的高级安全(t, n)阈值代理签名方案

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5422940

Raman Kumar, H. Verma

引用次数: 35

A weighted mean time Min-Min Max-Min selective scheduling strategy for independent tasks on Grid 网格上独立任务的加权平均时间Min-Min - Max-Min选择调度策略

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5423047

S. Chauhan, R. Joshi

引用次数: 63

Automated analysis of gestational sac in medical image processing 医学图像处理中妊娠囊的自动分析

2010 IEEE 2nd International Advance Computing Conference (IACC) Pub Date : 2010-03-01 DOI: 10.1109/IADCC.2010.5422938

V. Chakkarwar, M. Joshi, P. S. Revankar

{"title":"Automated analysis of gestational sac in medical image processing","authors":"V. Chakkarwar, M. Joshi, P. S. Revankar","doi":"10.1109/IADCC.2010.5422938","DOIUrl":"https://doi.org/10.1109/IADCC.2010.5422938","url":null,"abstract":"Ultrasonography is considered to be one of the most powerful techniques for imaging organs for an obstetrician and gynecologist. The first trimester of pregnancy is the most critical period in human existence. This evaluation of the first trimester pregnancy is usually indicated to confirm presence and number of pregnancy, its location and confirm well being of the pregnancy. The first element to be measurable is the gestational sac(gsac) of the early pregnancy. Size of gestational sac gives measure of fetus age in early pregnancy and also from that EDD is predicted. Today, the monitoring of gestational sac is done non-automatic, with human interaction. These methods involve multiple subjective decisions which increase the possibility of interobserver error. Because of the tedious and time-consuming nature of manual measurement, an automated, computer-based method is desirable which gives accurate boundary detection, consequently finding accurate diameter. Ultrasound images are characterized by speckle noise and edge information, which is weak and discontinuous. Therefore, traditional edge detection techniques are susceptible to spurious responses when applied to ultrasound imagery due to speckle noise. Algorithm for finding edges of gsac are as follows. In first step, we are using contrast enhancement, followed by filtering. We are smoothing image using lowpass filter followed by wiener filter. This image is segmented using thresholding. This results in image having large number of gaps due to high intensity around sac. These false regions are minimized by morphological reconstruction. Then boundaries are detected using morphological operations. Knowledge based filtering is used to remove false boundaries. In this prior knowledge of shape of gestational sac is used. First fragmented edges are removed then most circular shape is found as our sac is generally circular. Once sac is located, sac size is measured to predict the gestational age.","PeriodicalId":249763,"journal":{"name":"2010 IEEE 2nd International Advance Computing Conference (IACC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114861837","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: 10