| Paper: | WA-L6.1 |
| Session: | Implementation of Image and Video Processing Systems I |
| Time: | Wednesday, September 19, 09:50 - 10:10 |
| Presentation: |
Lecture
|
| Title: |
A PARALLEL CBIR IMPLEMENTATION USING PERCEPTUAL GROUPING OF BLOCK-BASED VISUAL PATTERNS |
| Authors: |
Shyi-Chyi Cheng; National Taiwan Ocean University | | |
| | Wei-Kan Huang; National Kaohsiung First University of Science & Technology | | |
| | Yu-Jhih Liao; National Kaohsiung First University of Science & Technology | | |
| | Da-Chun Wu; National Kaohsiung First University of Science & Technology | | |
| Abstract: |
This paper proposes a parallel solution to retrieve images from distributed data sources using perceptual grouping of block-based visual patterns. The method of grouping visual patterns into image model based on generalized Hough transform is one of the most powerful techniques for image analysis. However, real-time applications of this method have been prohibited due to the computational intensity in similarity searching from a large centralized image collection. A query object is decomposed into non-overlapped blocks, where each of them is represented as a visual pattern obtained by detecting the line edge from the block using the moment-preserving edge detector. A voting scheme based on generalized Hough transform is proposed to provide object search method, which is invariant to the translation, rotation, scaling of image data. In this work, we describe a heterogeneous cluster-oriented CBIR implementation. First, the workload to perform an object search is analyzed, and then, a new load balancing algorithm for the CBIR system is presented. Simulation results show that the proposed method gives good performance and spans a new way to design a cost-effective CBIR system. |
