This document summarizes an research paper on offline handwritten signature verification using local binary pattern features and K-nearest neighbors classification. It describes preprocessing signatures using Otsu thresholding, extracting local binary pattern features, and classifying signatures with KNN. 40 signature recognition approaches were reviewed before designing this system. The system achieved an accuracy of 85% on a dataset of bank cheque signatures during testing.