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Proceedings Paper

Real-time multi-core parallel image sharpness evaluation algorithm for high resolution CCD/CMOS based digital microscope autofocus imaging system
Author(s): Lei Zhang; Peng Liu; Yu-ling Liu; Fei-hong Yu
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Paper Abstract

Multi-core parallel computing is spreading in most industries and the imaging and machine vision industry is also taking the advantage of this technology. The utilization of parallel computing will increase the throughputs and reduce response times of the imaging system, especially for the high resolution CCD/CMOS based imaging system. Multi-core image processing fully utilizes the ability of the CPU's parallel computing, for multiple cores share the processing task of an imaging system. The parallel computing automatically detects the number of CPUs or the number of the CPU cores and then automatically splits the image into the according number of logical blocks, which will be then passed on to the processing threads separately. After all the processing threads finishes, the result will be synthesized. For high resolution CCD/CMOS based digital microscope autofocus imaging system, the speed of measuring the sharpness of the current collected image greatly affects the speed of the autofocus process. The real-time requirement of the system needs fewer time cost for image sharpness evaluation and the multi-core parallel computing is applied in the algorithm to meet this requirement. The proposed algorithm is as follows. First, the current collected image is divided into several logical blocks; second, for each block, a worker thread will compute the sharpness of this block; finally, after all the worker threads finishes, the sharpness will be summed for comparison with the next collected image. In order to test the efficiency of the algorithm, a dedicated high resolution CCD/CMOS based digital microscope autofocus imaging system is designed and implemented and several image sharpness evaluation algorithms are used, as well as the self-adaptive mountain-climbing search (SAMCS) method for the searching method. The numeric simulation and the experimental results show that the proposed algorithm greatly improves the speed of the autofocus process.

Paper Details

Date Published: 6 August 2009
PDF: 7 pages
Proc. SPIE 7384, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Imaging Detectors and Applications, 738415 (6 August 2009); doi: 10.1117/12.835288
Show Author Affiliations
Lei Zhang, Zhejiang Univ. (China)
Peng Liu, Zhejiang Univ. (China)
Yu-ling Liu, Zhejiang Univ. (China)
Fei-hong Yu, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 7384:
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Imaging Detectors and Applications

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