Read Image, Preprocess, Detect Edges, Binarization, Hough Transform for Circular Boundaries, and Edge Enhancement through Image Overlay

Throughout this process, you can follow these sequential steps for image processing: First, load the input image and perform preprocessing to optimize image quality. Next, detect edges and binarize the resulting image to facilitate better shape recognition. Subsequently, apply Hough transform to identify circular boundaries, which aids in precise target localization. Finally, overlay this processed image with the original to enhance edge visibility, making features more distinct.

It is worth noting that during image processing, various algorithms and techniques can be employed to achieve optimal results. For instance, the Canny edge detector can be used for robust edge detection, while the OTSU algorithm enables adaptive binary thresholding. Additionally, edge enhancement can be achieved using gradient-based methods like the Sobel operator or Laplacian-based approaches to sharpen edge contours.

In summary, by implementing preprocessing, edge detection, binarization, Hough transform, and edge enhancement, you can effectively identify and localize targets while improving overall image quality.