17 February 2006 Fast classification and segmentation of high-resolution images of multiple and complicated colonies
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Abstract
This paper presents a methodology for high resolution image classification and segmentation. The size and information volume of the images, taken by a high resolution digital camera, will be tens to hundreds times as the ones taken by an ordinary CCD camera. In order to speed up the image segmentation process of the large images, we classify the images first by using a low resolution image, then, segment them by a fast segmentation algorithm. The algorithm is studied mainly based on multi-resolution technique and the fusion of edge detection result and similarity segmentation result. By use this methodology, the whole image segmentation process time is reduced by tens' times than traditional segmentation methods. And the accuracy of the image segmentation is not decreased.
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Weixing Wang, Lei Li, "Fast classification and segmentation of high-resolution images of multiple and complicated colonies", Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640S (17 February 2006); doi: 10.1117/12.642391; https://doi.org/10.1117/12.642391
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