• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.1-8
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• 2008

In this paper, an algorithm to compensate the inter-view mismatch in the multi-view video according to the different characteristics of cameras is presented. Interview mismatches make it difficult to merge the multi-view images and decrease the coding performance. So, a preprocessing operation to compensate the mismatches is requisite in the multi-view video coding. It is shown that the mismatch in the outputs of multi-view cameras with different electro-optical transfer functions can be approximated with a linear model of a gain and an offset. In addition, a new algorithm for estimating and compensating the inter-view mismatch based on the detection of the overlapped region is presented. Experimental results using various rectified stereo images show that the proposed method compensates inter-view mismatches more accurately compared to the conventional approach.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.16-25
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• 2000

In this paper, a new disparity detection algorithm which is robust to noise is presented. It detects the disparity of an arbitrary pixel through the iterative competition with neighbor pixels in the range of disparity. A diffusion process to improve stereo matching confidence is used prior to detecting disparity of an arbitrary pixel. It is used for aggregating initial matching measure of the difference map. If the image region for matching is too small, a wrong match might be found due to noise. On the contrary, the region is too big, it results in blurring of object boundaries. Therefore, we decide the image region for matching by using the diffusion process for aggregating matching measure, then detect the true disparity with proposed competition method to the distribution of matching measure. Through the proposed method we get the result of improving matching rate of 6.96% with real stereo imge. From the simulation with the stereo imge, the proposed disparity detection method significantly outperforms the conventional method to matching rate.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1903-1904
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• 2008

이 논문에서는 영상 프레임사이의 움직임 벡터 연구에 기반을 둔 빠른 블록 정합 움직임 추정을 위해 보완된 다이아몬드 탐색 알고리즘을 제안한다. 실험 결과는 제안된 알고리즘이 기존의 다이아몬드 탐색 알고리즘 보다 더 적은 탐색으로 좀 더 빠르게 동작하는 것이 가능하다. 본 알고리즘의 특징은 움직임이 적은 블록에 대해서는 CDS(conjugate direction search) 알고리즘을 적용하여 탐색함으로써 탐색 점의 수를 줄일 수 있어 좀 더 빠르게 움직임 추정을 할 수 있다.

• Journal of IKEEE
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• v.20 no.4
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• pp.420-423
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• 2016

In this paper, we proposed an implementation of panoramic image stitching that operates in real time at the embedded environment by applying ROI based PROSAC algorithm using the directionality of the image. The conventional panoramic image stitching applies SURF or SIFT algorithm which contains unnecessary computation and a lots of data to detect feature points. In this paper, we use the direction of the input image and we proposed the method of reducing the unnecessary computation by using ROI. We use a gyro sensor and an acceleration sensor. Output data from gyro and acceleration sensors can be calibrated by complementary filter. The calibration does not affect the operating time of the proposed image stitching algorithm in embedded environment. Therefore, it is possible to operate in real-time.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.730-737
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• 2013

In this paper, Constrained One-Bit Transform (C1BT) based motion estimation using extension of matching error criterion is proposed. C1BT based motion estimation algorithm exploiting Number of Non-Matching Points (NNMP) instead of Sum of Absolute Differences (SAD) that used in the Full Search Algorithm (FSA) facilitates hardware implementation and significantly reduces computational complexity. However, the accuracy of motion estimation is decreased. To improve inaccurate motion estimation, this algorithm based motion estimation extending matching error criterion of C1BT is proposed in this paper. Experimental results show that proposed algorithm has better performance compared with the conventional algorithm in terms of Peak-Signal-to-Noise-Ratio (PSNR).

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.77-85
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• 2006

There is the spatial correlation of the video sequence between the motion vector of current blocks. In this paper, we propose the enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased properly of motion vectors. The proposed algorithm determines an exact motion vector using the predicted motion vector from the adjacent macro blocks of the current frame and the Cross-Hexagonal search pattern. From the of experimental results, we can see that our proposed algorithm outperforms both the prediction search algorithm (NNS) and the fast block matching algorithm (CHS) in terms of the search speed and the coded video's quality. Using our algorithm, we can improve the search speed by up to $0.1{\sim}38%$ and also diminish the PSNR (Peak Signal Noise Ratio) by at nst $0.05{\sim}2.5dB$, thereby improving the video qualify.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.45-52
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• 2004

According tothe development of digital media technologies various algorithms for video sequence matching have been proposed to match the video sequences efficiently. A large number of video sequence matching methods have focused on frame-wise query, whereas a relatively few algorithms have been presented for video sequence matching or video shot matching. In this paper, we propose an efficientalgorithm to index the video sequences and to retrieve the sequences for video sequence query. To improve the accuracy and performance of video sequence matching, we employ the Cauchy function as a similarity measure between histograms of consecutive frames, which yields a high performance compared with conventional measures. The key frames extracted from segmented video shots can be used not only for video shot clustering but also for video sequence matching or browsing, where the key frame is defined by the frame that is significantly different from the previous fames. Several key frame extraction algorithms have been proposed, in which similar methods used for shot boundary detection were employed with proper similarity measures. In this paper, we propose the efficient algorithm to extract key frames using the cumulative Cauchy function measure and. compare its performance with that of conventional algorithms. Video sequence matching can be performed by evaluating the similarity between data sets of key frames. To improve the matching efficiency with the set of extracted key frames we employ the Cauchy function and the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed method yields the high matching performance and accuracy with a low computational load compared with conventional algorithms.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.57-58
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• 2011

스테레오 정합 방법에는 크게 영역기반 방식과 특징기반 방식으로 나뉠수 있으며 보통 사용자가 특징점을 입력해야 하는 특징기반보다는 광범위하게 사용할 수 있는 영역기반 방식의 스테레오 정합법이 많이 사용되고 있다. 하지만 영역기반은 해당 영역 즉 블록 단위로 비교를 해야 하기 때문에 실시간 스테레오 정합에는 계산 시간이 많이 걸리게 된다. 따라서 본 연구에서 제안하는 Line Disparity Map 알고리즘은 정합 점을 라인별로 비교하기 때문에 블록 방식보다 빠르고, 라인의 기울기를 바탕으로 정합점을 찾기 때문에 주변환경에 영향을 받지 않는 장점이 있다.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.99-107
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• 2004

In stereo matching system, it is efficient using segment patch, which divides the image into homogeneous region in color or similar intensity, because it preserves the disparity boundary and disparity continuity in low textured region. But many miss matching occur in the highly textured region because of the over segmentation that makes patch small and ambiguous. In this paper, in order to solve problems, we propose adaptive patch matching based on the watershed image segmentation. Performance was verified in experimental results.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.176-183
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• 2013

We propose a rolled fingerprint merging algorithm that effectively merges plain fingerprints in consecutive frame units that are fed through rolling and detects more fingerprint minutiae in order to increase the fingerprint recognition rate. The proposed rolled fingerprint merging algorithm uses a adaptive projection mask; it contains a detector that separates plain fingerprints from the background and a projection mask generator that sequentially projects the detect ed images. In addition, in the merging unit, the pyramid-shaped projection method is used to detect merged rolled fingerprints from the generated variable projective mask, starting from the main images. Simulations show that the extracted minutia e are 46.79% more than those from plain fingerprints, and the proposed algorithm exhibits excellent performance by detecting 52.0% more good fingerprint minutiae that are needed for matching.