• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.44-47
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• 1991

There exists a transform trellis code that is optimal for stationary Gaussian sources and the squared-error distortion measure at all rates. In this paper, we train an asymptotically optimal version of such a code to obtain one which is matched better to the statistics of real world data. The training algorithm uses the M-algorithm to search the trellis codebook and the LBG-algorithm to update the trellis codebook. To adapt the codebook for the varying input data. we use two gain-adaptive methods. The gain-adaptive scheme 1, which normalizes input block data by its gain factor, is applied to images at rate 0.5 bits/pixel. When each block is encoded at the same rate, the nonstationarity among the block variances leads to a variation in the resulting distortion from one block to another. To alleviate the non-uniformity among the encoded image, we design four clusters from the block power, in which each cluster has its own trellis codebook and different rates. The rate of each cluster is assigned through requiring a constant distortion per-letter. This gain-adaptive scheme 2 produces good visual and measurable quality at low rates.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.767-774
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• 1990

Successive images can be reconstructed without great degradation by using one codebook in vector quantization, because statistics of successive images are sinilar. In this paper, we propose a method to update vector centroids in one slot of an image sequence and reconstruct images with the codebook replenished with the updated vector centroids. To remove the overhead required to transmit the updated vector centroids, we catagorize image blocks into changing blocks and nonchanging blocks, and then transmit only the labels of the changing blocks. Therefore, we can assign the remaining bits to the replenishment of a codebook. By the proposed method, almost the same image as the same image as the one reconstructed by LBG algorithm can be obtained and the bit rate can be reduced to below 0.5 bit/pixel.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2287-2290
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• 2003

In this paper, an image vector quantization method is proposed not only to improve the compression ratio but also to reduce the computation cost. The proposed method could save the computation cost of codebook generation and encoding by using the modified LBG algorithm of Partial Search Partial Distortion (PSPD) in wavelet domain, by which the code book was constructed together with the partial codebook search, the partial code vector elements, and the interruption criterion. We have designed and implemented the vector quantizer to verify the improvement in reducing compression ratio in encoding processing and reducing the computation cost.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.7-11
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• 2002

In this study, fur the shape-based image retrieval, a method using local differential invariants is proposed. This method calculates the differential invariant feature vector at every feature point extracted by Harris comer point detector. Then through vector quantization using LBG algorithm, all feature vectors are represented by a codebook index. All images are indexed by the histogram of codebook index, and by comparing the histograms the similarity between images is obtained. The proposed method is compared with the existing method by performing experiments for image database including various 1100 trademarks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1596-1603
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• 2000

In this paper an image coding scheme using the correlation of neighboring VQ indices in wavelet domain is proposed. The codewords in each sub-codebook are reordered in ascending order according to their energy in order to inmcrease the dependency of the indices. And the relative dresses of the reordered indices are transmitted to a receiver instead of to absolute addresses. LBG algorithm is used for obtaining a multiresolution codebool and PNN using k-d tress used for generating its initial values. Our experimental results show that the proposed coding scheme outperforms JPEG and an ordinary wavelet-VQ method at low-bit rates in terms of PSNR.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.157-157
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• 1999

Researches on the gesture recognition have become a very interesting topic in the computer vision area, Gesture recognition from visual images has a number of potential applicationssuch as HCI (Human Computer Interaction), VR(Virtual Reality), machine vision. To overcome thetechnical barriers in visual processing, conventional approaches have employed cumbersome devicessuch as datagloves or color marked gloves. In this research, we capture gesture images without usingexternal devices and generate a gesture trajectery composed of point-tokens. The trajectory Is spottedusing phase-based velocity constraints and recognized using the discrete left-right HMM. Inputvectors to the HMM are obtained by using the LBG clustering algorithm on a polar-coordinate spacewhere point-tokens on the Cartesian space .are converted. A gesture vocabulary is composed oftwenty-two dynamic hand gestures for editing drawing elements. In our experiment, one hundred dataper gesture are collected from twenty persons, Fifty data are used for training and another fifty datafor recognition experiment. The recognition result shows about 95% recognition rate and also thepossibility that these results can be applied to several potential systems operated by gestures. Thedeveloped system is running in real time for editing basic graphic primitives in the hardwareenvironments of a Pentium-pro (200 MHz), a Matrox Meteor graphic board and a CCD camera, anda Window95 and Visual C++ software environment.