• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.55-61
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• 2015

In this paper, we introduce a method to synthesize realistic make-up effects on input images efficiently. In particular, we focus on shading on the make-up effects due to the lighting and face curvature. By doing this, we can synthesize a wider range of effects realistically than the previous methods. To do this, the information about lighting information together with the normal vectors on all pixels over the face region in the input image. Since the previous methods that compute lighting information and normal vectors require relatively heavy computation cost, we introduce an approach to approximate lighting information using cascade pose regression process and normal vectors by transforming, rendering, and warping a standard 3D face model. The proposed method consumes much less computation time than the previous methods. In our experiment, we show the proposed approximation technique can produce naturally looking virtual make-up effects.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.292-300
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• 2008

An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.136-144
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• 2001

visual cryptography is a simple method in which secret information can be directly decoded in human visual system without any cryptographic computations. This scheme is a kind of secret sharing scheme in which secret of image type is distributed to n random image(we call it share). When the secret image is distributed to n shares, the original pixel is expanded as much as the size of column in basis matrix. It causes the deterioration of contrast in docoded secret image. Therefore, many researches have performed to reduce the size of pixel expansion and to improve the contrast by overlapping the row in basis matrix for (k, n) visual cryptography. In addition, we show that the proposed method can construct the (k, n) visual cryptography with multiple contrasts depending on selecting k out of n slides in a group.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.6
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• pp.15-26
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• 2001

Visual cryptography is a simple method in which secret information can be directly decoded in human visual system without any cryptographic computations. When the secret image is scattered to n random shares(slides), this scheme has some week point such as pixel expansion and contrast degradation. Therefore, it is necessary to reduce the pixel expansion and improve the contrast in recovered image. In this paper, we propose a new construction method for (k, n) visual cryptography using the cumulative matrix. In case k is odd, we can construct the cumulative matrix perfectly. For even k, the contrast of special pair in decoded image can be achieved best by permitting multiple contract. The proposed method is more simple than that of S. Droste\`s in construction and the average contrast of decoded image is improved for the most part. Also, we show that the basis matrices depending on the cumulative matrix are able to be applied for the general access structure.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.21-30
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• 1990

This paper describes a hardware implementation of the interframe monochrome video CODEC using a MC-CVQ(Motion Compensated and Classified Vector Quantization) algorithm. The specifications of this CODEC are (1) the resolution of image is $128{\times}128$ pixels, and (2) the transmission rates are about 10frames/sec at the 64Kbps channel. In order to design the CODEC under these conditions, it is implemented by a multiprocessor system composed of MC unit, CVQ nuit and decoder unit, which are controlled by microprogramming technique. And the 3~stage pipelined ALU(Arithmetic and Logic Unit) is adopted to calculate the minimum error distance in the MC unit and CVQ nuit. The realized system shows that the transmission rates are 6-15 frames/sec according to the relative motion of the video signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1809-1818
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• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.