Neural Networks, IEEE - INNS - ENNS International Joint Conference on
Download PDF

Abstract

In a previous paper [24], fast PCA implementation for face detection based on cross-correlation in the frequency domain between the input image and eigenvectors was presented. Here, this approach is developed to reduce the computation steps required by fast PCA. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single fast PCA processor. In contrast to using only fast PCA, the speed up ratio is increased with the size of the input image when using fast PCA and image decomposition. Simulation results demonstrate that our proposal is faster than the conventional and Fast PCA. Moreover, experimental results for different images show good performance.
Like what you’re reading?
Already a member?Sign In
Member Price
$11
Non-Member Price
$21
Add to CartSign In
Get this article FREE with a new membership!

Related Articles