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Study of the Haar Wavelet Feature Detector for Image Retrieval  

Peng, Shao-Hu (Dept of Electronic Engineering, Inha University)
Kim, Hyun-Soo (Dept of Electronic Engineering, Inha University)
Muzzammil, Khairul (Dept of Electronic Engineering, Inha University)
Kim, Deok-Hwan (Dept of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.47, no.1, 2010 , pp. 160-170 More about this Journal
Abstract
This paper proposes a Haar Wavelet Feature Detector (HWFD) based on the Haar wavelet transform and average box filter. By decomposing the original image using the Haar wavelet transform, the proposed detector obtains the variance information of the image, making it possible to extract more distinctive features from the original image. For detection of interest points that represent the regions whose variance is the highest among their neighbor regions, we apply the average box filter to evaluate the local variance information and use the integral image technique for fast computation. Due to utilization of the Haar wavelet transform and the average box filter, the proposed detector is robust to illumination change, scale change, and rotation of the image. Experimental results show that even though the proposed method detects fewer interest points, it achieves higher repeatability, higher efficiency and higher matching accuracy compared with the DoG detector and Harris corner detector.
Keywords
Interest point; Haar wavelet; Feature detector; Object recognition;
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Times Cited By KSCI : 2  (Citation Analysis)
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