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Algorithm to extract the shortest linear edge and the longest diagonal of single isolated human insulin crystals for in-situ microscopy

In this contribution, an algorithm is presented, which is able to extract the shortest linear edge and the longest diagonal of each single isolated human insulin crystal region, which is found in an arbitrary image captured by an insitu microscope inside of a reactor, where a human insulin crystallization processes is taking place. First, the image regions of the single isolated crystals are segmented by combining three different techniques: thresholding, single nearest prototype classification and snakes. Then, the image positions of the vertices of each single isolated crystal region are determined by using the Hough Transformation. Finally, both the shortest linear edge and the longest diagonal of each single isolated crystal region are extracted by measuring and comparing distances between the found image positions of the single isolated crystal region vertices. Experimental results revealed an absolute length error of 4.18 percent and 2.32 percent of the extracted shortest linear edges and the extracted longest diagonals, respectively.