Sign Language Detection Using open-cv and Haar cascade
Sign Language Detection Using open-cv python Haar Cascade classifiers are an effective way for object detection. This method was proposed by Paul Viola and Michael Jones in their paper Rapid Object Detection using a Boosted Cascade of Simple Features . The algorithm implemented in OpenCV can also be used to detect other things, as long as you have the right classifiers. My OpenCV distribution came with classifiers for eyes, upper body, hands, frontal face and profile face. Haar Cascade is a machine learning-based approach where a lot of positive and negative images are used to train the classifier. Frequently used keywords haar Positive Images: These images contain the images which we want our classifier to identify. Negative Images: Images of everything else, which do not contain the object we want to detect. Features Initially, the algorithm needs a lot of positive images (images of hand) and negative images (images without hand) to train the classifier. Then we need to extract