Age Group Estimation by Combining Texture and Fractal Analysis
نویسنده
چکیده
In this paper the age group estimation is presented based on combination of texture and fractal dimension features. The age of the human is used as one of the important key parameter for computer vision applications. The fractal dimension of the face image and the texture analysis is used to classify the age of the person into the three different groups such as child(10-20), young(21-50) and old(51 and above. The proposed approach of combing the fractal and texture features shows an effective estimation of the age group. The facial age groups are estimated with 90% average accuracy. General Terms Image Processing, Age Group Estimation, Texture Analysis, Fractal dimensions
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