Fusion of color histogram and LBP-based features for texture image retrieval and classification
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Author list: Liu P., Guo J.-M., Chamnongthai K., Prasetyo H.
Publisher: Elsevier
Publication year: 2017
Journal: Information Sciences: Informatics and Computer Science Intelligent Systems Applications (0020-0255)
Volume number: 390
Start page: 95
End page: 111
Number of pages: 17
ISSN: 0020-0255
Languages: English-Great Britain (EN-GB)
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Abstract
The Local Binary Pattern (LBP) operator and its variants play an important role as the image feature extractor in the textural image retrieval and classification. The LBP-based operator extracts the textural information of an image by considering the neighboring pixel values. A single or join histogram can be derived from the LBP code which can be used as an image feature descriptor in some applications. However, the LBP-based feature is not a good candidate in capturing the color information of an image, making it is less suitable for measuring the similarity of color images with rich color information. This work overcomes this problem by adding an additional color feature, namely Color Information Feature (CIF), along with the LBP-based feature in the image retrieval and classification systems. The CIF and LBP-based feature adequately represent the color and texture features. As documented in the experimental result, the hybrid CIF and LBP-based feature presents a promising result and outperforms the existing methods over several image databases. Thus, it can be a very competitive candidate in retrieval and classification application. ฉ 2017 Elsevier Inc.
Keywords
Color information feature, Local binary pattern
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