Generalized Hough Transform VLSI Processor for Model-Based Edge Detection

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概要

• 論文の詳細を見る

• Edge detection is essential in the image processing such as pattern recognition, scene analysis, etc, but it is difficult to perform edge detection completely on a noisy image. To overcome this, we have proposed a modelbased edge detection system in which some models are selected from an incomplete input image (bottom-up procedure) and a determination of a model through a verification process (top-down procedure). For selecting the models in such a system, Generalized Hough Transform (GHT) is an appropriate solution, because it can find a known-object even at occluded or bad condition. However, GHT requires high computational power and large memory capacity for finding an appropriate candidate from all the models. In this article, we propose a design of VLSI processor for high-speed GHT. The proposed GHT processor is based on the concept that each candidate edge element in the given image is computed by shift operations in the parameter space. Using a new memory architecture with parallel read/write operations for one word of the memory cells, the processor can quickly determine the most likely models. As a result, the processor is compact in size and to be able to work 7500 times faster than its software implementation on workstation.

• 社団法人電子情報通信学会の論文
• 1994-09-26

著者

• Kameyama Michitaka

  Graduate School of Information Sciences, Tohoku University

• Hanyu Takahiro

  Graduate School of Information Sciences, Tohoku University

• Hanyu Takahiro

  Graduate School Of Information Sciences Tohoku University

• Kameyama Michitaka

  Graduate School Of Information Science Tohoku University

• Yusuf Muhammad

  Graduate School of Information Sciences,Tohoku University

• Yusuf Muhammad

  Graduate School Of Information Sciences Tohoku University

• Kameyama Michitaka

  Graduate School of Information Sciences,Tohoku University

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