{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:03:12Z","timestamp":1760709792822,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,12,27]],"date-time":"2018-12-27T00:00:00Z","timestamp":1545868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["105-2410-H-126 -005 -MY3"],"award-info":[{"award-number":["105-2410-H-126 -005 -MY3"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/sym11010021","type":"journal-article","created":{"date-parts":[[2018,12,27]],"date-time":"2018-12-27T11:29:43Z","timestamp":1545910183000},"page":"21","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Content-Based Color Image Retrieval Using Block Truncation Coding Based on Binary Ant Colony Optimization"],"prefix":"10.3390","volume":"11","author":[{"given":"Yan-Hong","family":"Chen","sequence":"first","affiliation":[{"name":"School of Information, Zhejiang University of Finance &amp; Economics, Zhejiang 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chin-Chen","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Feng Chia University, Taichung 40724, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4480-7351","authenticated-orcid":false,"given":"Chia-Chen","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Computer Science, Providence University, Taichung 43301, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng-Yi","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Feng Chia University, Taichung 40724, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1109\/TCOM.1979.1094560","article-title":"Image compression using block truncation coding","volume":"27","author":"Delp","year":"1979","journal-title":"IEEE Trans. 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