OpenCV: Inconsistent Output of Contour Detection with Varying Thresholding Methods
I'm trying to debug I'm working on a personal project and I'm currently working on a project where I need to detect contours in images using OpenCV, but I'm facing inconsistent results depending on the thresholding method I choose. While using `cv2.threshold` with a simple binary threshold works reasonably well, switching to `cv2.adaptiveThreshold` results in missing several contours in darker areas of my images. I’ve tried adjusting the block size and C parameter in adaptiveThreshold, but the outcome remains unsatisfactory. Here's a minimal example of what I've implemented: ```python import cv2 import numpy as np # Load the image image = cv2.imread('test_image.jpg', cv2.IMREAD_GRAYSCALE) # Simple binary thresholding _, binary_thresh = cv2.threshold(image, 127, 255, cv2.THRESH_BINARY) contours_binary, _ = cv2.findContours(binary_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Adaptive thresholding adaptive_thresh = cv2.adaptiveThreshold(image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2) contours_adaptive, _ = cv2.findContours(adaptive_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Count contours detected print(f'Contours detected with binary threshold: {len(contours_binary)}') print(f'Contours detected with adaptive threshold: {len(contours_adaptive)}') ``` When I run this code, I get a significantly lower number of contours detected with the adaptive method, especially in darker regions of the image. The output is: ``` Contours detected with binary threshold: 12 Contours detected with adaptive threshold: 5 ``` I'm using OpenCV version 4.5.1 and Python 3.8. I've ensured that the input image is pre-processed to remove noise, but I suspect that the issue might stem from how adaptive thresholding handles pixel intensity variations. Is there a specific configuration or pre-processing step I might be missing to improve contour detection in darker areas or a better approach to handle such cases? Any insights or best practices would be greatly appreciated! I'm working on a service that needs to handle this. I recently upgraded to Python stable.