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Study for Embedded Colony Algorithm Based on Morphological Technology

The fast image processing based on iterative erosion principle can complete separation of colony image of adhesion target quickly. This algorithm is composed of local threshold method of image binarization; the morphological processing, analyzing; removing the edge based on Hough Transform and using improved iterative erosion algorithm to adhesion target segmentation and counting. The algorithm has scale invariance and self-adaption for recognition different size colony target. The conditional expansion algorithm designed in the paper can effectively modify the count mistakes which are caused by fragments formed by the segmentation of large size targets in the iterative and erosion processes. The algorithm has been applied in portable colony counting instrument on ARM11 embedded platform. Twenty heterotrophic bacterial samples have been tested in experiments. The results show that this algorithm can realize the image segmentation rapidly and effectively and the time of analysis is less than 2 seconds. The images edge detection rate can reach 100%. The detection accuracy can get the requirements of GB 4789.2-2010 and achieve deviation of 3% in colonies’ total number less than 300CFU.The applied of algorithm is widely in the similar particle image analysis system.