Recognition of Gender Based on Facial Features Fixation using Cosfire Filters

Recognition of the gender based on computer vision is an important application in security, retail advertising and marketing fields. Faces of humans provide important visual information for gender perception .The main motive of this paper is to classify the gender of the human beings based on facial features by using COSFIRE filters. In this paper, the Viola Jones algorithm is used to detect the face of the human beings and to extract the features. The features that are extracted are then applied to COSFIRE filters for classification. The COSFIRE filter compares feature extracted with data base images and then gives the classification of the gender that is male or female. This technique is utilized as a part of different applications like shape identification, and in biometric frameworks that are genuine applications. This strategy gives exact outcomes as contrast with different procedures like HOG and LBP. Besides, we utilize GENDER-FERET DATASET for assessment. Support vector machines (SVM) is utilized as a classifier with a specific end goal to assess the gender of the images.