文章基本信息

标题：An Image Indexing and Retrieval Method Using Local Tetra Pattern for Content-Based Image Retrieval (CBIR)
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作者：Shraddha D. Jumade ; Prof. Sheetal S. Dhande
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：3
页码：2061-2064
出版社：TechScience Publications
摘要：Content-Based Image Retrieval gives the path to retrieve the needed information based on the image content. Here, we propose a novel image indexing and retrieval algorithm using Local Tetra Pattern (LTrP) for Content- Based Image Retrieval (CBIR). The earlier versions of Content-Based Image Retrieval (CBIR) was based on Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Ternary Pattern (LTP). These methods encode the relationship between the referenced pixel and its surrounding neighbors by computing gray-level difference. These methods extract information based on the distribution of edges, which are coded using only two directions. The performance of these methods are little less and thus it can be improved by differentiating the edges in more than two directions. The proposed method encodes the relationship between the referenced pixel and its neighbors, based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions. The performance is increased by differentiating the edges in four direction code, so called Local Tetra Pattern (LTrP) for Content- Based Image Retrieval (CBIR).
关键词：Content-Based Image Retrieval (CBIR); Local;Binary Pattern (LBP); Local Tetra Pattern (LTrP).