• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.258-263
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• 2006

Each pixel in a matching block does not equally contribute to block matching and the matching error is greatly affected by image complexity. On the basis of the facts, this paper proposes a fast motion estimation algorithm using some sub-blocks selected by the image complexity. The proposed algorithm divides a matching block into 16 sub-blocks, computes the image complexity in every sub-block, executes partial block matching using some sub-blocks with large complexity, and detects a motion vector. The simulation results show that the proposed algorithm brings about negligible image degradation, but can reduce a large amount of computation in comparison with conventional algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1671-1689
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• 2013

The key issue of block-based multi-focus image fusion is to determine the size of the sub-block because different sizes of the sub-block will lead to different fusion effects. To solve this problem, this paper presents a novel genetic algorithm (GA) based multi-focus image fusion method, in which the block size can be automatically found. In our method, the Sum-modified-Laplacian (SML) is selected as an evaluation criterion to measure the clarity of the image sub-block, and the edge information retention is employed to calculate the fitness of each individual. Then, through the selection, crossover and mutation procedures of the GA, we can obtain the optimal solution for the sub-block, which is finally used to fuse the images. Experimental results show that the proposed method outperforms the traditional methods, including the average, gradient pyramid, discrete wavelet transform (DWT), shift invariant DWT (SIDWT) and two existing GA-based methods in terms of both the visual subjective evaluation and the objective evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.628-633
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• 2010

This paper proposes a block matching algorithm to improve the sub-block matching algorithm that uses partial sub-blocks being a great contribution to the block matching. Unlike the conventional algorithm using the one sub-block group the proposed algorithm uses two sub-block groups. The matching using the small group selects a candidate block to be a good possibility of a similar block with a small computation cost and the additional matching using the large group in the selected block decreases a wrong matching. Simulation results show that the proposed algorithm always has good image quality at the same computation cost as compared to the conventional algorithm and it has an outstanding performance at the matching using a few sub-blocks.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.367-369
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• 2001

멀티미디어 환경의 발전에 따라 동영상에 대한 효과적인 검색 및 관리와 CG와 일반 영상의 합성을 위하여 영상 내의 카메라 동작 요소 검출 기법이 필요하다. 본 논문에서는 sub-block당 투영 영상을 이용만 카메라 동작 요소 검출 방법을 제안한다. 제안한 방법은 sub-block당 평균값을 이용만 투영 영상상에서 각 sub-block 내에서의 x, y 방향 이동 성분을 구하여 이를 통한 Optical flow를 얻는다. 제안하는 방법은 기존의 block-matching을 통하여 optical flow를 얻는 방법보다 계산량의 감소와 계산 속도의 증가를 나타낸다. 실험 결과에서는 제안하는 방법에 의하여 얻은 optical flow를 보여주며 예측도의 증가를 보여준다.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.417-420
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• 2006

Detection of faces on still color images with arbitrary backgrounds is attempted in this paper. The newly proposed method is invariant to arbitrary background, number of faces, scale, orientation, skin color, and illumination through the steps of color clustering, cluster scanning, sub-block processing, face area detection, and face verification. The sub-block method makes the proposed method invariant to the size and the number of faces in the image. The proposed method does not need any pre-training steps or a preliminary face database. The proposed method may be applied to areas such as security control, video and photo indexing, and other automatic computer vision-related fields.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.949-955
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• 2005

In this Paper, we propose fast block matching algorithm by dividing complex areas based on complexity order of reference block and square sub-block to reduce an amount of computation of full starch(FS) algorithm for fast motion estimation, while keeping the same prediction quality compared with the full search algorithm. By using the fact that matching error is proportional to the gradient of reference block, we reduced unnecessary computations with square sub-block adaptive matching scan based image complexity instead of conventional sequential matching scan and row/column based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination(PDE) algorithm without any prediction quality, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.487-490
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• 2011

This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1703-1708
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• 2005

This paper proposes a modified block matching algorithm which reduces an amount of matching computation by using only pixels contributing greatly to block matching. In consideration of algorithm implementation and additional informatirm, the proposed algorithm divides a matching block into sub-blocks, selects some sub-blocks using their complexities, and execute the block mating with them. Simulation results show that the proposed algorithm performs a valid block matching, diminishing computation cost.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.4
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• pp.68-75
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• 2008

This paper proposes a new data hiding method for binary images using the weighting value of pixel-value differencing. The binary cover image is partitioned into non-overlapping sub-blocks and find the most suitable position to embed a secret bit for each sub-block. The proposed method calculates the weighted value for a sub-block to pivot a pixel to be changed. This improves the image quality of the stego-image. The experimental results show that the proposed method achieves a good visual quality and high capacity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.55-63
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• 2000

This paper investigated the sub-region compression effect of the three dimensional DCT(3D-DCT) using the difference component(DC) of inter-frame in images. The proposed algorithm are the method that obtain compression effect to divide the information into subband after 3D-DCT, the data appear the type of cubic block(8${\times}$8${\times}$8) in eight difference components per unit. In the frequence domain that transform the eight differential component frames into eight DCT frames with components of both spatial and temporal frequencies of inter-frame, the image data are divided into frame component(8${\times}$8 block) of time-axis direction into 4${\times}$4 sub block in order to effectively obtain compression data because image components are concentrate in corner region with low-frequency of cubic block. Here, using the weight of sub block, we progressed compression ratio as consider to adaptive sub-region of low frequency part. In simulation, we estimated compression ratio, reconstructed image resolution(PSNR) with the simpler image and the complex image contained the higher frequency component. In the result, we could obtain the high compression effect of 30.36dB(average value in the complex-image) and 34.75dB(average value in the simple-image) in compression range of 0.04~0.05bpp.