Abstract
Automated human face detection is a topic of significant interest in the field of image processing and computer vision. In the last years much emphasis has been on using facial images to extract gender of human which has become much used in many modern programs used in mobile phones. Local Binary Pattern (LBP), Local Directional Pattern (LDP) and Local Ternary Pattern (LTP) are popular appearance-based methods for extracting the feature from images. This paper proposes an improved Local Ternary Pattern technique called Dynamic Local Ternary Patterns to address the problem of gender classification using frontal facial images. The proposed Dynamic Local Ternary Patterns solve the limitation found in LBP (poorly performed in illumination variation and random noise) and LDP (produces inconsistence pattern), by increasing the number of the face components, applying the four cardinal directions namely North, East, West, South and using a dynamic threshold in LTP instead of a static one.
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