AGE GROUP CLASSIFICATION USING HAAR FEATURES EXTRACTION AND KNN

Recognition of the one of the most facial varieties, for example, OCR(character), expression and gender has been broadly contemplated. Programmed age group and foreseeing future countenances have once in a while been investigated. With the progression in age of a human there occurs some changes in the face features. This paper worries with giving a procedure to gauge age gathering utilizing face features. This procedure includes three stages: Location, Feature Extraction and Classification. The geometric components of facial pictures like wrinkle topography, face edge, left eye to right eye separation, eye to nose separation, eye to jaw separation and eye to lip separation are computed. Taking into account the surface and shape data age grouping is done utilizing K-Means bunching calculation. Age reaches are ordered progressively relying upon number of gatherings utilizing K-Means bunching calculation. The acquired results were huge. This paper can be utilized for anticipating future confronts, arranging gender orientation, and expression recognition from facial images.