Browsing by Author "Su, CK"

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A study on Chinese carbon-signature recognition
(2002-03-01)
Lin, SF
;
Chang, YW
;
Su, CK
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A novel off-line algorithm and a modified chain code for recognizing signatures are proposed in the present study. Carbon paper is used to detect force distributions when people write their signatures. First of all, the signature contours are located and the upper and lower profiles are generated then, these are used to classify the given si.-nature. Both the gray-scale and the chain code characteristics of a signature are used to extract structure and force distribution features, which are then transformed into a normalized vector. Finally, a Supervised Fuzzy Adaptive Hamming Network (SFAHN) is employed to interpret the feature vector in order to determine whether the signature is genuine or not. Simulation results show that the proposed algorithm has a good recognition rate.
An automatic focusing algorithm
(2002)
Lin, SF
;
Lin, YT
;
Su, CK
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A simple and effective automatic focusing algorithm is proposed in this article. The principle of the proposed automatic focusing algorithm is based on that, for the radial test pattern, a best-focused image should have the smallest blurred region in the middle of the acquired image, and hence, should have the smallest equivalent radius. The circular Hough transform has became a common method in numerous image-processing applications for circle detection. Various modifications to the basic circular Hough transform have been suggested, such as: the inclusion of edge orientation, simultaneous consideration of a range of circle radii, the use of a complex accumulator array with the phase proportional to the log of the radius, or for filter operations. The purpose of this work is to show that a radius of a circular region extracted by a normalized circular Hough transform is a possible solution for determining the sharpness of images. To acquire high quality images with a given CCD camera, it is crucial that the camera be located exactly at the back length of the lens, i.e., the focus position of the lens. In the best conditions, the contours of the acquired images are of the sharpest, with none of the blurring effects associated with unfocused images. Acquiring such high quality images by these means is the main goal of the automatic focusing algorithm proposed in this article. (C) 2003 Wiley Periodicals, Inc.
Wavelet tree classification and hybrid coding for image compression
(2005-12-01)
Su, CK
;
Hsin, HC
;
Lin, SF
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A hybrid coding system that uses a combination of set partition in hierarchical trees (SPIHT) and vector quantisation (VQ) for image compression is presented. Here, the wavelet coefficients of the input image are rearranged to form the wavelet trees that are composed of the corresponding wavelet coefficients from all the subbands of the same orientation. A simple tree classifier has been proposed to group wavelet trees into two classes based on the amplitude distribution. Each class of wavelet trees is encoded using an appropriate procedure, specifically either SPIHT or VQ. Experimental results show that advantages obtained by combining the superior coding performance of VQ and efficient cross-subband prediction of SPIHT are appreciable for the compression task, especially for natural images with large portions of textures. For example, the proposed hybrid coding outperforms SPIHT by 0.38 dB in PSNR at 0.5 bpp for the Bridge image, and by 0.74 dB at 0.5 bpp for the Mandrill image.