文章基本信息

标题：Object Recognition Using Texture Based Analysis
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作者：Mansi Saraswat ; Anil Kumar Goswami ; Aastha Tiwari 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2013
卷号：4
期号：6
页码：775-782
出版社：TechScience Publications
摘要：Object recognition plays an important role in the area of image processing and target based applications. In order to identify an object we must have its features in the form of a feature vector. This can be achieved by feature extraction. There are various ways of extracting features of an image. It can be based on color, texture or shape. The aim of this paper is to study and compare the different texture based approaches for object recognition and feature extraction. GLCM and Haar wavelet transform are the most primitive methods for texture analysis. In this paper two more techniques based on their fusion have been considered. These techniques have been tested on sample images and their detailed experimental results along with the method of implementation have been discussed.
关键词：GLCM; Haar; fusion; texture; object recognition