Edge Detection with Canny and Hough Transform

This function performs edge detection. It first loads the image, then converts it to grayscale, and applies the Canny edge detection algorithm. Optionally, it can apply non-maximum suppression and Hough transform to detect lines in the image.

Technology Stack : OpenCV, NumPy

Code Type : Image processing

Code Difficulty : Intermediate

                
                    
def edge_detection(image_path, threshold=100, non_max_suppression=True):
    import cv2
    import numpy as np

    # Load the image
    image = cv2.imread(image_path)
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Apply Canny edge detection
    edges = cv2.Canny(gray, threshold, threshold * 2, apertureSize=3, L2gradient=True)

    # Optionally apply non-maximum suppression
    if non_max_suppression:
        edges = cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
        linesP = cv2.HoughLinesP(edges, 1, np.pi/180, threshold, None, minLineLength=100, maxLineGap=10)
        if linesP is not None:
            for line in linesP:
                x1, y1, x2, y2 = line[0]
                cv2.line(edges, (x1, y1), (x2, y2), (255, 0, 0), 2)

    return edges