<![CDATA[The detection of red and white blood cells in microscopic blood images is an important task in medical diagnosis, particularly in the identification of diseases such as anemia, leukemia, and infections. However, the manual process of detecting blood cells is often time-consuming and prone to human error. This research aims to develop an automated method of detecting blood cells in microscopic images using an adaptive edge detection approach with the Prewitt operator. Digital image processing is used to improve the quality of microscopic blood images to make them easier to analyze. The proposed adaptive edge detection method is designed to adjust the detection sensitivity based on image characteristics, such as contrast and noise, resulting in more accurate and efficient detection. Experiments were conducted on a set of microscopic images containing red and white blood cells with varying image quality. Experimental results show that this method Keywords Edge Detection, Prewitt Operator, Blood Cells]]>
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