Building a Web-based Document Scanner: Tackling Perspective and Shadows with OpenCV

We've all been there: you need to scan a receipt or a signed document, but all you have is your phone. You take a photo, but it's skewed, shadowy, and looks nothing like a real "scan." I decided to solve this by building DocuScanPro, a web-based document scanner that focuses on high-fidelity image enhancement directly in the browser. The Problem: Perspective and Lighting Standard mobile photos suffer from two major issues: Perspective Distortion: When you don't take the photo perfectly from above. Uneven Lighting: Shadows from your hand or environmental lighting that make the text hard to read. The Solution: A Python + OpenCV Pipeline To tackle this, I built a backend processing engine using FastAPI and OpenCV. Here’s a high-level look at the pipeline: Finding the Document We use Canny edge detection followed by contour approximation to identify the four corners of the document. python Simple example of findContours in OpenCV contours, _ = cv2.findContours(edged, cv2.RETR_LIST, cv2.CHA