一种新的图像压缩与模式匹配算法

2013 Third International Conference on Advances in Computing and Communications Pub Date : 2013-08-29 DOI:10.1109/ICACC.2013.52

P. Shamna, C. Tripti, P. Augustine

{"title":"一种新的图像压缩与模式匹配算法","authors":"P. Shamna, C. Tripti, P. Augustine","doi":"10.1109/ICACC.2013.52","DOIUrl":null,"url":null,"abstract":"The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. Compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for pattern recognition encryption techniques.","PeriodicalId":109537,"journal":{"name":"2013 Third International Conference on Advances in Computing and Communications","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Algorithm for Image Compression and Pattern Matching\",\"authors\":\"P. Shamna, C. Tripti, P. Augustine\",\"doi\":\"10.1109/ICACC.2013.52\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. Compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for pattern recognition encryption techniques.\",\"PeriodicalId\":109537,\"journal\":{\"name\":\"2013 Third International Conference on Advances in Computing and Communications\",\"volume\":\"137 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Third International Conference on Advances in Computing and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACC.2013.52\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Third International Conference on Advances in Computing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACC.2013.52","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

随着通信和多媒体应用的发展，对存储和传输大型图像数据库产生了巨大的需求。当前的通信系统需要压缩技术来以适当的方式存储和传输数据。图像压缩方案可以用较少的计算复杂度来管理高灵敏度的数据。本文提出了一种新的图像压缩和模式匹配算法，称为差分分量分析(DCA)。DCA提取最相关的图像特征组件来识别图像。DCA的前提是匹配的图像具有最小的差异成分。利用1000多张人脸图像进行了DCA实验。结果表明，该方法可以将图像压缩为单个十进制值，并且使用较少的计算步骤。该概念可应用于模式识别加密技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Novel Algorithm for Image Compression and Pattern Matching

The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. Compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for pattern recognition encryption techniques.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2013 Third International Conference on Advances in Computing and Communications

自引率

0.00%

发文量