I would check out template matching or using OpenCV feature extractors such as SIFT, SURF, ORB Template Matching scans an image with your template, smaller ima

I would check out template matching or using OpenCV feature extractors such as SIFT, SURF, ORB Template Matching scans an image with your template, smaller image and finds the location with highest cross correlation: https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_template_matching/py_template_matching.html https://opencv-python-tutroals.readthedocs.io/en/latest/py_t... Template matching assumes the example image wont deform or take on different orientations. Popular Feature Extraction finds and derive more robust features that help find objects in the scenarios of distortion, orientation, and scale. Link for feature detection and matching: https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_feature2d/py_matcher/py_matcher.html https://opencv-python-tutroals.readthedocs.io/en/latest/py_t... Pyimagesearch does a cool method where they enable template matching to work at different scales. It ignores color information (by using edge detection), which could be a critical feature if the object has specific color: https://www.pyimagesearch.com/2015/01/26/multi-scale-template-matching-using-python-opencv/ https://www.pyimagesearch.com/2015/01/26/multi-scale-templat...