Browsing by Author "CHENG, SC"

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A NEURAL-NETWORK IMPLEMENTATION OF THE MOMENT-PRESERVING TECHNIQUE AND ITS APPLICATION TO THRESHOLDING
(1993-04-01)
CHENG, SC
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TSAI, WH
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資訊工程學系
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Department of Computer Science
A neural-network implementation of the moment-preserving technique which is widely used for image processing is proposed. The moment-preserving technique can be thought of as an information transformation method which groups the pixels of an image into classes. The variables in the so-called moment-preserving equations are determined iteratively by a recurrent neural network and a connectionist neural network which work cooperatively. Both of the networks are designed in such a way that the sum of square errors between the moments of the input image and those of the output version is minimized. The proposed neural network system is applied to automatic threshold selection. The experimental results show that the system can threshold images successfully. The performance of the proposed method is also compared with those of four other histogram-based multilevel threshold selection methods. The simulation results show that the proposed technique is at least as good as the other methods.
DUAL-ALU CRISC ARCHITECTURE AND ITS COMPILING TECHNIQUE
(1991)
CHOU, HC
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CHUNG, CP
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CHENG, SC
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資訊科學與工程研究所
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Institute of Computer Science and Engineering
As semiconductor technology advances, more devices can be accommodated in a single VLSI chip. The feasibility of putting multifunctional units in a chip is then worth studying. Such an approach, however, will face software and hardware difficulties (and also tradeoffs). CRISC is a 32-bit single-chip VLSI processor architecture achieving high performance by means of RISC and multiple functional unit approaches. Dual-ALUs are used to execute instructions concurrently for fine-grained parallelism. Up to three instructions can be executed simultaneously by CRISC. Here, CRISC architecture design considerations and instruction cache scheme are investigated. Final microarchitecture and its incorporated software technique to produce object code for fine-grained parallel execution are described; its upper bound performance is estimated by an architectural model. A preliminary evaluation of the CRISC is also conducted, showing most satisfying results.
IMAGE COMPRESSION BY MOMENT-PRESERVING EDGE-DETECTION
(1994-11-01)
CHENG, SC
;
TSAI, WH
;
資訊工程學系
;
Department of Computer Science
A new image compression algorithm based on a new edge detection technique is proposed. A given image is compressed by dividing the image into non-overlapping square blocks and coding the edge information in each non-uniform block. The edge feature in a given window is detected by applying the moment-preserving principle to the image data. The edge directions are approximated by multiples of 45-degrees to speed up the direction process without introducing obvious distortion. For a larger block size, a more accurate model of a two-step edge is employed in the detection process. The proposed algorithm offers excellent reconstructed image quality agreeing with human perception, high compression ratios, and greatly reduced coding complexity. The solution to the edge detection problem in a given block is also analytic. The algorithm can be performed very fast for real-time applications with no need for special hardware.