This paper presents an enhanced multiband feature technique to improve the performance of face recognition under varying illumination. First, the illumination invariant subbands are extracted using wavelet packet transform and multiband feature selector. Then, histogram equalization is applied to the selected subbands to enhance the contrast of the subband (global). To reduce the noise and enhance the fine details of the facial features (local), an unsharp filter is subsequently applied to the histogram equalized subband. The unsharp filter is created by combining a Gaussian low pass filter and a negative Laplacian operator. The recognition performance of the proposed enhancement scheme is validated against the Yale B database. An improvement in recognition rate has been observed when the enhancement scheme is compared to the original unenhanced subband.
|Title of host publication||IEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010 - Conference Booklet|
|Number of pages||4|
|Publication status||Published - 01 Dec 2010|
|Event||IEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010 - Kuala Lumpur, Malaysia|
Duration: 20 Nov 2010 → 21 Nov 2010
|Conference||IEEE Conference on Sustainable Utilization and Development in Engineering and Technology 2010, STUDENT 2010|
|Period||20/11/10 → 21/11/10|