The proposed work is an attempt to investigate the compatibility of enhancement and segmentation within the digital image processing framework in the medical field. The correction nonuniform illumination enhancement technique and marker-controlled watershed segmentation method were conducted in order to calculate the red blood cells in digital images of blood samples. Twenty-five patients at Medical City Teaching Hospital in Baghdad participated in this study. The attained outcomes of the two mentioned methods were compared with the real results, which were obtained by a digital camera coupled with a high technology microscope. The comparison illustrated large matching between two proposed techniques and real outcomes throughout very short computation time in spite of limited features of the used computer and available MATLAB environment.
This paper include the problem of segmenting an image into regions represent (objects), segment this object by define boundary between two regions using a connected component labeling. Then develop an efficient segmentation algorithm based on this method, to apply the algorithm to image segmentation using different kinds of images, this algorithm consist four steps at the first step convert the image gray level the are applied on the image, these images then in the second step convert to binary image, edge detection using Canny edge detection in third Are applie the final step is images. Best segmentation rates are (90%) obtained when using the developed algorithm compared with (77%) which are obtained using (ccl) before enhancement.
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