Local texton XOR patterns: A new feature descriptor for content-based image retrieval

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• 作者：Anu Bala^a ; ^{abala022@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Tajinder Kaur^b
• 关键词：Texton ; Local XOR patterns ; Local binary patterns ; Histogram ; Texture ; Image retrieval
• 刊名：Engineering Science and Technology,an International Journal
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：19
• 期：1
• 页码：101-112
• 全文大小：7333 K

文摘

In this paper, a novel feature descriptor, local texton XOR patterns (LTxXORP) is proposed for content-based image retrieval. The proposed method collects the texton XOR pattern which gives the structure of the query image or database image. First, the RGB (red, green, blue) color image is converted into HSV (hue, saturation and value) color space. Second, the V color space is divided into overlapping subblocks of size 2 × 2 and textons are collected based on the shape of the textons. Then, exclusive OR (XOR) operation is performed on the texton image between the center pixel and its surrounding neighbors. Finally, the feature vector is constructed based on the LTxXORPs and HSV histograms. The performance of the proposed method is evaluated by testing on benchmark database, Corel-1K, Corel-5K and Corel-10K in terms of precision, recall, average retrieval precision (ARP) and average retrieval rate (ARR). The results after investigation show a significant improvement as compared to the state-of-the-art features for image retrieval.