Browsing by Author "Seenam Amir, Sajid Naeem and Muhammad Umer"

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    (2018) Seenam Amir, Sajid Naeem and Muhammad Umer
    The study proposes effective and time efficient face recognition system. The proposed method uses a hybrid form of approach which uses Haar- like features. These features are extracted by applying Voila Jones algorithm. Subsequently Local Binary Pattern Histograms is used to train on these features. The data used for experimentation is obtained from Yale University. It includes normal as well as face that are difficult to identify. The difficulty is due to varying amount of light and variation in poses. The distinguishing feature of proposed approach in comparison to conventional approaches is found to be stable and highly accurate. On top of it, it increases the number of images (frames) processed per second. This frame rate, is observed to be 40 which is quite high when compared with the conventional approaches.