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Visual Quality Improvement for ordered dither block truncation coding

电脑学刊 2019年第1期30卷 15-22页

作者： Chyi-Hwa Chu

ordered dither block truncation coding (ODBTC) employs the ordered dither technique to produce the bitmap required in traditional block truncation coding (BTC). It can reduce the complexity of computations in the coding phrase. However, the blocking artifacts and undesired noises are still in the decoded images by ODBTC. In this paper, the properties of thresholds stored in the dither matrices are considered to estimate the decoded pixel intensities. That is, the dither matrices are used in both coding and decoding. Experimental results tell that the proposed schema can not only reduce quantization error but also improve the visual quality for the reconstructed images by ODBTC.

关键词： block truncation coding digital halftoning image compression ordered dither block truncation coding ordered dither technique

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Content-Based Image Retrieval with ordered dither block truncation coding Features

Content-Based Image Retrieval with Ordered Dither Block Trun...

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IEEE International Conference on Image Processing

作者： Jing-Ming Guo Heri Prasetyo Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781479923427

This paper presents a technique for Content-Based Image Retrieval (CBIR) by exploiting the low complexity advantage of the ordered-dither block truncation coding (ODBTC) for generating image content descriptors. The two image features, namely Color Co-occurrence Feature (CCF) and Bit Pattern Features (BPF), are generated from ODBTC encoded data streams (without really performing an image compression or decoding process) to measure the similarity between two images. Experimental results show that the proposed method is superior to the block truncation coding (BTC) image retrieval system and other former methods, and prove that the ODBTC scheme is not only suited for image compression for its simplicity, but also offers a conveniently way for image indexing in the content-based image retrieval system.

关键词： ordered dither block truncation coding Content-Based Image Retrieval Color Co-occurrence Feature Bit Pattern Feature content-based image retrieval Image compression Data compression block truncation coding image retrieval image indexing dithering Band-pass filters

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Image retrieval using indexed histogram of Void-and-Cluster block truncation coding

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SIGNAL PROCESSING 2016年 123卷 143-156页

作者： Guo, Jing-Ming Prasetyo, Heri Lee, Hua Yao, Chen-Chieh Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This paper presents a simple approach to improve the image retrieval accuracy in the Void-and-Cluster block truncation coding compressed domain. The proposed approach directly derives an image descriptor from the ordered dither block truncation coding (ODBTC) data stream without performing the decoding process. The Color Histogram Feature (CHF) is generated from the two ODBTC color quantizer, while the Halftoning Local Derivative Pattern (HLDP) is constructed from the ODBTC bitmap image. The similarity between two images are measured from their CHF and HLDP features. Three schemes are involved to improve the image retrieval accuracy, including the similarity weight optimization, feature reweighting, and user relevance feedback optimization. An evolutionary stochastic algorithm is exploited to optimize the similarity weight and feature weight in the nearest neighbor distance computation, as well as in the query update of relevance feedback optimization. Section 5 shows that the proposed scheme yields a promising result, and thus it can be a very effective candidate in addressing the content based image retrieval and image classification task. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Content-based image retrieval ordered dither block truncation coding Similarity weight Feature reweighting Relevance feedback

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Content-Based Image Retrieval Using Features Extracted From Halftoning-Based block truncation coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2015年第3期24卷 1010-1024页

作者： Guo, Jing-Ming Prasetyo, Heri Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei 10607 Taiwan

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.

关键词： Bit pattern feature color co-occurrence feature content-based image retrieval ordered dither block truncation coding

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Image indexing using the color and bit pattern feature fusion

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2013年第8期24卷 1360-1379页

作者： Guo, Jing-Ming Prasetyo, Heri Su, Huai-Sheng Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan

This paper presents a new way to index a color image by exploiting the low complexity of the ordered-dither block truncation coding (ODBTC) for generating the image features. Image content descriptor is directly constructed from two ODBTC quantizers and the corresponding bitmap image without performing the decoding process. The color co-occurrence feature (CCF) derived from the ODBTC quantizers captures the color distribution and image contrast in block based manner, while the Bit Pattern Feature (BPF) characterizes image edges and visual patterns. The similarity between two images can be easily determined based on their CCF and BPF under a specific distance metric measurement. A metaheuristic algorithm, namely Particle Swarm Optimization (PSO), is employed to find the optimum similarity constants and improve the retrieval accuracy. Experimental results demonstrate that the proposed indexing method is superior to the former block truncation coding (BTC) image retrieval system and the other existing methods. The ODBTC method offers an effective way to index an image in a content-based image retrieval system, and simultaneously it is able to compress an image efficiently. Thus, this system can be a very competitive candidate in image retrieval applications. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Content-based image retrieval Image indexing ordered dither block truncation coding Particle Swarm Optimization (PSO)

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Video retrieval framework based on color co-occurrence feature of adaptive low rank extracted keyframes and graph pattern matching

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INFORMATION PROCESSING & MANAGEMENT 2022年第2期59卷 102870-102870页

作者： Mallick, Ajay Kumar Mukhopadhyay, Susanta Indian Sch Mines Indian Inst Technol Dept Comp Sci & Engn Dhanbad 826004 Jharkhand India

In recent times, exploration of multimedia required ever increasing demand and application for intelligent video retrieval from repositories. This paper presents an efficient video retrieval framework by employing the effective singular value decomposition and computationally low complex ordered dither block truncation coding to extract simple, compact, and well discriminative Color Co-occurrence Feature (CCF). In this context, the occurrence probability of a video frame pixel in the neighborhood is employed to formulate this specific and distinct feature. Moreover, we applied a new adaptive low rank thresholding based on energy concentricity, transposition, and replacement invariance characteristics to formulate a unified fast shot boundary detection approach to solve the protuberant bottleneck problem for realtime cut and gradual transition that eventually contributes for effective keyframes extraction. Therefore, we can assert that the keyframes are distinct and discriminative to represent the whole video content. For effective indexing and retrieval, it is imperative to formulate similarity score evaluator for the encapsulated contextual video information with substantial temporal consistency, least computation, and post-processing. Therefore, we introduced graph-based pattern matching for video retrieval with an aim to sustain temporal consistency, accuracy and time overhead. Experimental results signify that the proposed method on average provides 7.40% and 17.91% better retrieval accuracy and 23.21% and 20.44% faster than the recent state-of-the-art methods for UCF11 and HMDB51 standard video dataset, respectively.

关键词： Content based video retrieval Color Co-Occurrence Feature Shot boundary detection Keyframe extraction Graph based matching ordered dither block truncation coding

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