Abstract
In this paper, we propose a content-based image retrieval (CBIR) approach using color and texture features extracted from block truncation coding based on binary ant colony optimization (BACOBTC). First, we present a near-optimized common bitmap scheme for BTC. Then, we convert the image to two color quantizers and a bitmap image-utilizing BACOBTC. Subsequently, the color and texture features, i.e., the color histogram feature (CHF) and the bit pattern histogram feature (BHF) are extracted to measure the similarity between a query image and the target image in the database and retrieve the desired image. The performance of the proposed approach was compared with several former image-retrieval schemes. The results were evaluated in terms of Precision-Recall and Average Retrieval Rate, and they showed that our approach outperformed the referenced approaches.
Highlights
Block Truncation Coding (BTC) is a classic technique for image compression [1]
We introduce an approach for retrieving images that enhances the performance of the content-based image retrieval (CBIR) using color and texture features extracted based on binary ant colony optimization (BACOBTC)
The proposed BACOBTC [28] method introduces a BTC technique based on binary ant colony optimization (BACO) in order to get images that have good visual quality
Summary
Block Truncation Coding (BTC) is a classic technique for image compression [1]. An improved BTC scheme based on a set of pre-defined bit planes has been proposed [4] In this method, a Huffman compress algorithm is used to reduce the bit rate. Guo et al [9,10,11,12] presented several approaches to retrieve color images utilizing the features extracted from improved block truncation coding. Keker et al [15] discussed a novel image retrieval technique, which is based on the slope magnitude method with block truncation coding and the shape features. We introduce an approach for retrieving images that enhances the performance of the CBIR using color and texture features extracted based on binary ant colony optimization (BACOBTC).
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