Content-Based Image Retrieval Using Features Extracted From Halftoning-Based Block Truncation Coding
This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers an...
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| Published in | IEEE transactions on image processing Vol. 24; no. 3; pp. 1010 - 1024 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
United States
IEEE
01.03.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers and bitmap image. Two image features are proposed to index an image, namely, color co-occurrence feature (CCF) and bit pattern features (BPF), which are generated directly from the ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two ODBTC quantizers and bitmap, respectively, by involving the visual codebook. Experimental results show that the proposed method is superior to the block truncation coding image retrieval systems and the other earlier methods, and thus prove that the ODBTC scheme is not only suited for image compression, because of its simplicity, but also offers a simple and effective descriptor to index images in CBIR system. |
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| AbstractList | This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers and bitmap image. Two image features are proposed to index an image, namely, color co-occurrence feature (CCF) and bit pattern features (BPF), which are generated directly from the ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two ODBTC quantizers and bitmap, respectively, by involving the visual codebook. Experimental results show that the proposed method is superior to the block truncation coding image retrieval systems and the other earlier methods, and thus prove that the ODBTC scheme is not only suited for image compression, because of its simplicity, but also offers a simple and effective descriptor to index images in CBIR system.This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers and bitmap image. Two image features are proposed to index an image, namely, color co-occurrence feature (CCF) and bit pattern features (BPF), which are generated directly from the ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two ODBTC quantizers and bitmap, respectively, by involving the visual codebook. Experimental results show that the proposed method is superior to the block truncation coding image retrieval systems and the other earlier methods, and thus prove that the ODBTC scheme is not only suited for image compression, because of its simplicity, but also offers a simple and effective descriptor to index images in CBIR system. This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers and bitmap image. Two image features are proposed to index an image, namely, color co-occurrence feature (CCF) and bit pattern features (BPF), which are generated directly from the ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two ODBTC quantizers and bitmap, respectively, by involving the visual codebook. Experimental results show that the proposed method is superior to the block truncation coding image retrieval systems and the other earlier methods, and thus prove that the ODBTC scheme is not only suited for image compression, because of its simplicity, but also offers a simple and effective descriptor to index images in CBIR system. |
| Author | Jing-Ming Guo Prasetyo, Heri |
| Author_xml | – sequence: 1 surname: Jing-Ming Guo fullname: Jing-Ming Guo email: jmguo@seed.net.tw organization: Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan – sequence: 2 givenname: Heri surname: Prasetyo fullname: Prasetyo, Heri email: heri_inf_its_02@yahoo.co.id organization: Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25420264$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Arrays Band-pass filters Bit Pattern Feature Color Co-occurrence feature Content-Based Image Retrieval Feature extraction Image coding Image color analysis Image retrieval Indexing Ordered Dither Block Truncation Coding |
| Title | Content-Based Image Retrieval Using Features Extracted From Halftoning-Based Block Truncation Coding |
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