MATLAB Implementation for Digital Image Processing: Chromosome Counting through Edge Detection and Morphological Operations

This MATLAB-based digital image processing program analyzes chromosome images by implementing edge detection algorithms (such as Canny or Sobel), morphological operations including erosion and dilation, and advanced techniques like opening and closing operations to accurately count chromosome numbers. The primary objective is to apply computer vision techniques for chromosome image analysis, where the program extracts edge information using gradient-based methods, removes noise through morphological filtering, and achieves precise chromosome counting through connected component analysis. This technology holds significant potential in biomedical applications, enabling researchers and medical professionals to better understand chromosome structures and abnormalities, thereby supporting disease diagnosis and treatment planning. The implementation provides flexibility through adjustable parameters for thresholding, structuring element size, and iteration counts, allowing optimization for various chromosome image types and analysis requirements. Key MATLAB functions employed include edge() for detection, imerode() and imdilate() for morphological processing, and bwlabel() for component labeling and counting.