Face Recognition Using Featured Histogram
Abdul Wahid Ansari · 2013
Abstract — Face recognition system is a computer application for automatically identifying or verifying a person from a digital image from a source. One of the ways to do this is by comparing selected facial features from the image and a facial database. Face recognition involves three steps: Face Detection, Feature Extraction and Matching. Face detection method detect face area from the image using Viola-jones with computer vision, and some feature like eye, nose and mouth is extracted. The approach uses a set of local features that are easy to calculate and robust to partial occlusions. Histogram for each feature is calculated and used as a matching factor for recognition. The paper explores the use of local feature histograms for feature-based recognition of objects from database images. Since it only requires the calculation of very simple features, it is extremely fast and achieves more accurate recognition performance. The results show that the proposed method is with precision of 97 % for the recognition of faces. Keywords—Face detection, Feature extraction, Histogram matching, Face recognition.