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5 March 1999 Efficient shape transformations on a massively parallel processor
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Proceedings Volume 3646, Nonlinear Image Processing X; (1999)
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
One of the most important features in image analysis is shape. Problems regarding shape are widely encountered in image processing applications, such as machine vision recognition, visually guided robots, analysis of biomedical images, etc. Mathematical morphology is the branch of image processing that deals with shape analysis. The definition of all morphological transformations is based on two primitive operations, namely dilation and erosion. Since many applications require the solution of morphological problems in real time, the efficient implementation of these operations, in terms of computational time, is crucial. In this paper, two algorithms for the dilation and erosion on an advanced associative processor are presented and evaluated. It is shown that these algorithms can take full advantage of the capabilities of the advanced architecture. Specifically, the ability to access all memory words in parallel leads to synchronous rapid execution of any image translation dictated by the structuring elements employed for morphological processing. The interconnection network allows the efficient implementation of image translations at any number of pixels. Also, the ability to perform logic operations parallel on the bits in each processing element leads to optimal computational complexity. Finally, it is shown that there is a trade-off between circuit complexity and communication delay.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andreas I. Svolos, Charalampos Konstantopoulos, and Christos Kaklamanis "Efficient shape transformations on a massively parallel processor", Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999);

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