Shooting Target Detection

I am looking for an experienced Computer Vision Engineer to build a robust c++ script that automatically detects and maps the scoring rings on a B27 shooting target from standard smartphone photos. "i want it in c++" The End Goal: Given a photo of a used B27 shooting target (taken at various angles and lighting conditions), the script must automatically correct the perspective, locate the target, and accurately identify/draw the scoring rings (X, 10, 9, 8, 7) so that bullet impacts can eventually be scored. The Challenges (Why this isn't a basic OpenCV tutorial): Bullet Holes: The paper is covered in bullet holes. Traditional edge detection (like finding the white rings using Canny/Hough) often fails because the bullet holes destroy the lines. Perspective Distortion: Photos are taken by users holding their phones, so the paper is often skewed or angled. The algorithm must automatically find the paper boundaries and warp it flat. Ring Shapes: The B27 rings are not perfect ellipses. They are superellipses (Lamé curves with power n=4). Standard [login to view URL] will fail to match the corners. What the Algorithm Needs to Do (Scope of Work): Take an image path as input via CLI. Step 1: Automatically detect the physical paper boundary and apply perspective correction (homography) to flatten the image. Step 2: Locate the center of the target (e.g., by finding the human silhouette/shoulders/head, which are rarely destroyed by bullets). Step 3: Accurately project or detect the scoring boundaries (superellipses) over the image, completely ignoring the noise from bullet holes. Step 4: Output a new image with the rings perfectly highlighted/drawn

Project ID: 40441539