Advanced Saliency Extraction Techniques Based on Principal Component Analysis and Boundary Information
Date Issued
2012
Date
2012
Author(s)
Chen, Chien-Chi
Abstract
Research of saliency map detection has fast development in the last ten years because of the great demand of image processing application, for instance image segmentation, image compression and image resizing etc. Saliency map, defining salient region of image automatically, has been indispensible part of preprocessing method in several image processes.
In past decade, saliency map has developed four primary concepts in the field such as the following: region-based, block-based, center-surround and object classification methods. Region-based method shows the robust performance during the recent year which is contrary to center-surround method. This is due to different image segmentation method, it can complement each methods.
According to the theorem, we focus on the region-based and block-based method for saliency detection. Region-based method is adopted image segmentation for preprocessing determining the salient regions, which can combine different segmentation methods with several concepts for enhancing diverse image. On the other hand, block-based method which calculates difference of each 8x8 block in image determining seldom appearing patches in high score to be a salient patch. In this thesis, we provide two novel methods below: First, a mixed region-based method which improves the state-of-the-art RC method into a region-based system with background determination concept. Second, the combination of region-based and block-based methods uses both advantages of two leading to a novel region-based method in our system.
The simulation results show that our two novel methods have better performance compared to different methods in saliency detection field.
Subjects
Saliency map
Saliency detection
Object detection
Type
thesis
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