Shape Recognition in Images using MATLAB: Circles, Rectangles, Squares, and More

This project involves developing a MATLAB program to identify geometric shapes such as circles, rectangles, and squares within images. The implementation leverages image processing algorithms and pattern recognition techniques to accurately detect and classify different shapes. Key steps typically include preprocessing operations like noise reduction and edge detection using functions such as imgaussfilt() and edge() with Canny or Sobel methods. Shape discrimination may involve techniques like Hough transform for circle detection (imfindcircles()), contour analysis (bwboundaries()), and geometric property calculations (regionprops() for area, perimeter, and eccentricity). This shape recognition technology has broad applications in computer vision and image processing domains, including object detection, automated inspection systems, and industrial quality control. By utilizing MATLAB for image-based shape recognition, we can rapidly and precisely identify various shapes in images, providing a foundation for subsequent image analysis and processing tasks. The code typically incorporates morphological operations, thresholding techniques, and feature extraction routines to enhance recognition accuracy across diverse image conditions.