| Paper: | IMDSP-P12.8 | ||
| Session: | Feature Extraction and Analysis | ||
| Time: | Thursday, May 18, 16:30 - 18:30 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Feature Extraction and Analysis | ||
| Title: | A New Adaptive Lifting Scheme Transform For Robust Object Detection | ||
| Authors: | Mahdi Amiri, Hamid Rabiee, Sharif University of Technology, Iran | ||
| Abstract: | This paper presents a new adaptive lifting scheme transform for detecting user-selected objects in a sequence of images. In our algorithm, we first select a set of object features in the wavelet transform domain and then build a new transform by using the selected features. The new wavelet transform is constructed based on adaptive prediction in a lifting scheme procedure. Adaptive prediction is performed such that, the large coefficients in the high-pass component of the old transform vanishes in the high-pass component of the new transform. Finally, both the old and new transforms are applied to a given test image and the transform domain coefficients are compared for detecting the object of interest. It is shown that the presented algorithm is robust to the noisy environments with reasonable signal-to-noise ratio. We have verified our claims with experimental results on noisy 1-D signals and images. | ||
©2018 Conference Management Services, Inc. -||- email: webmaster@icassp2006.org -||- Last updated Friday, August 17, 2012