Computer Vision and Machine Learning are two domains that are upcoming and helpful in the modern era. Computer Vision is a science that is designed to try to make a computer as good as a human. Machine Learning helps improve computer vision by training it to improve every time it is used. This paper presents a model of Support Vector Machine (SVM) with the AdaBoost classifier, which has proven results in recognizing different types of patterns. In this model, SVM is used as a recognizer. This model automatically extracts features from the raw images and generates predictions. The results are subject to experiments conducted on the well-known MNIST digit database

Computer Vision, Machine Learning, Classifier, SVM, Digit Recognition

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