2014 Fifth International Conference on Signal and Image Processing最新文献_第6页

Novel Restoration Process for Degraded Image 一种新的退化图像恢复方法

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.18

Tripty Singh

{"title":"Novel Restoration Process for Degraded Image","authors":"Tripty Singh","doi":"10.1109/ICSIP.2014.18","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.18","url":null,"abstract":"Restoration techniques of degraded image is still a challenging task, in spite of the sophistication of the recently proposed methods. All show an outstanding performance when the image model corresponds to the algorithm assumptions but fail to retain the edges and fine structure. In this paper, a novel approach for image restoration has been developed. To show the analysis of performance of this noel restoration procedure GUI has been developed. It shows the Restoration of Degraded image on various noises by different Filters. In implementation of the approach first, image is degraded by adding different types of noises in sample images and then convolving images with different kinds of filters (Mean Filters, Min and Max Filters). Proposed image restoration method's analysis on performances of denoising techniques Graphical User Interface has been developed as a part of this research. In this paper true colour sample images are degraded with different noise and then is restored back. The performance analyis of the present approach with state of art techniques are in terms of mean square error, peak signal-to-noise ratio, and normalized absolute error is also provided. In comparisons with other state of art methods, present approach yields better to optimization, and shows to be applicable to a much wider range of noises.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128152908","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: 13

A Novel and Efficient Algorithm to Recognize Any Universally Accepted Braille Characters: A Case with Kannada Language 一种新的有效的通用盲文识别算法:以卡纳达语为例

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.52

C. N. R. Kumar, S. Srinath

{"title":"A Novel and Efficient Algorithm to Recognize Any Universally Accepted Braille Characters: A Case with Kannada Language","authors":"C. N. R. Kumar, S. Srinath","doi":"10.1109/ICSIP.2014.52","DOIUrl":"https://doi.org/10.1109/ICSIP.2014.52","url":null,"abstract":"A Braille document image is a collection of dots. The position of the dot and relative-ness of the dot with other dots gives different Braille characters. It is challenging, to separate the character lines, words and characters from a Braille document. This paper presents an Optical Braille character recognition system for both machine punched and hand punched Kannada Braille text documents [21]. Standard spacing between the characters and lines are used to segregate the dots. Dot mesh is created and character box is identified. Once character box is identified an efficient look up method is designed to identify the equivalent normal Kannada character. A unique value for the Braille character is generated and the Braille character is matched to the corresponding normal Kannada character in one shot. A Braille character is made of 6 dots combination and hence only 26=64 different combinations are possible. Recognized character is classified into one of the 64 possible classes. Identifying the dot position inside a character box is done using the dot mesh and by computing the centre position of all the objects inside the character box.","PeriodicalId":111591,"journal":{"name":"2014 Fifth International Conference on Signal and Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128960928","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

Comprehensive Analysis of Object Detection through Segmentation 基于分割的目标检测综合分析

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.32

P. Nikkam, N. Hegde, Eswar Reddy

引用次数: 2

Offline Signature Verification Using Support Vector Machine 支持向量机离线签名验证

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.5

Kruthi C, Deepika C Shet

引用次数: 28

A Tour into Ambient Energy Resources and Battery Optimization 环境能源和电池优化之旅

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2014-01-08 DOI: 10.1109/ICSIP.2014.60

Ruchi Sharma, Shalini Prasad, S. Balaji

引用次数: 4

Object Based Image Retrieval from Database Using Combined Features 基于对象的组合特征数据库图像检索

2014 Fifth International Conference on Signal and Image Processing Pub Date : 2013-08-23 DOI: 10.1109/ICSIP.2014.31

H. Kavitha, M. Sudhamani, S. Omar, G. Ismail, A. S. Ghanem

引用次数: 19