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Face is an identity to recognize a person, everyone can recognize faces well and distinguish individual faces that had been identified previously in any circumstances, however whether a computer system is able to do the same as humans? The matters should be studied and developed. One of ways to identify the face image is by extracting features including Statistic Feature, Feature Haralic and DCT (Discrete Cosine Transform). It is very necessary to analyze the performance of the three methods by determining which one has better value in pattern recognition of face image, the object that will be recognized is the object of the face image with the number of samples is 1400 images with seven categories: face image with orientation 15 ? to left, 0 ? and 15 ? to right. The first stage that will be carried out is the process of grayscale and continued with the performance of feature extraction that is the performance of statistics feature (Feature Order One) with a level of accuracy of 65.54% , Performance Haralic Feature (Feature Order Two) with the level of accuracy of 50.89%, a combination of performance of Discrete Cosine Transform (DCT) with Statistics feature (feature Order One) with a level of accuracy of 7:14%, and performance of combination of Discrete Cosine Transform (DCT) with Haralic feature (feature Order Two) with the level of accuracy of 11.6%.
Face Statistic Feature Feature Haralic DCT (Discrete Cosine Transform).
Face Statistic Feature Feature Haralic DCT (Discrete Cosine Transform).
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