Enhancement of the Adaptive Shape Variants Average Values by Using Eight Movement Directions for Multi-Features Detection of Facial Sketch

Arif Muntasa, Mochammad Kautsar Shopan, Mauridhi Hery Purnomo, Kondo Kunio

Abstract


This paper aims to detect multi features of a facial sketch by using a novel approach. The detection of multi features of facial sketch has been conducted by several researchers, but they mainly considered frontal face sketches as object samples. In fact, the detection of multi features of facial sketch with certain angle is very important to assist police for describing the criminal’s face, when criminal’s face only appears on certain angle. Integration of the maximum line gradient value enhancement and the level set methods was implemented to detect facial features sketches with tilt angle to 15 degrees. However, these methods tend to move towards non features when there are a lot of graffiti around the shape. To overcome this weakness, the author proposes a novel approach to move the shape by adding a parameter to control the movement based on enhancement of the adaptive shape variants average values with 8 movement directions. The experimental results show that the proposed method can improve the detection accuracy up to 92.74%.


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References


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DOI: http://dx.doi.org/10.5614%2Fitbj.ict.2012.6.1.1

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