MATLAB Code Implementation for Image Processing Sequence

The image processing sequence is a crucial step in computer vision applications. This process typically involves using edge detection algorithms like Canny or Sobel operators to identify boundaries in digital images. Once boundaries are detected, the implementation calculates curvature along the boundary curves to locate inflection points - critical positions where the curve changes direction. The code then processes the boundary coordinates using vector operations to eliminate duplicate points, often through Euclidean distance thresholding or unique coordinate filtering. These optimization steps ensure precise boundary representation and reduce computational redundancy. The complete MATLAB implementation would involve functions like edge() for boundary detection, polyfit() for curve analysis, and unique() for coordinate deduplication. This sequential approach guarantees accurate image processing results with clean, well-defined boundaries, making it essential for feature extraction and image analysis tasks.