Abstract
Parasitical diseases are among the first cause of hospitalization and mortality. The diagnostics of intestinal parasitical diseases is based on stools specimens test through the microscopic image. The manual evaluation of microscopic images is time consuming and depends on the human expert. Digital images are extensively used in medicine for diagnostic and also for survey guidance. We present in this work a method of parasite extraction from microscopic images. The extraction scheme has four main steps: The first step is the edge detection using the multi-scale wavelet transform. The second step uses edges to locate the region of interest on the image by looking for the round or approximately round objects through the Hough transform. The circles detected by the Hough transform are used as the initial contour for the active contour. The third step applied an active contour model to locate the contour of the parasite. The last step uses this contour to extract the parasite through the logic operation with the original image and the mask corresponding to the interior of the contour. Experimental results show that the proposed scheme is very efficient for the extraction of parasite from the stools images. It has accurate segmentation ability despite of the poor quality or complex background of microscopic stools images.
Keywords: Extraction, gradient vector flow snake, hough transform, intestinal parasites, microscopic images, segmentation.
Graphical Abstract
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