Title :
Regions of Interest extraction based on visual attention model and watershed segmentation
Author :
Zhang, Jing ; Zhuo, Li ; Shen, Lansun
Author_Institution :
Signal & Inf. Process. Lab., Beijing Univ. of Technol., Beijing
Abstract :
The presented research addressed a novel visual attention model and watershed segmentation based approach of regions of interest (ROIs) extraction, which automatically extracts ROIs and copes with the watershed over-segmentation. This approach uses visual attention model to locate salient points, in which the winner point, the most salient point, is selected as the seed point of watershed segmentation. ROIs are extracted by combining salient regions with watershed segmented regions. The focus of attention (FOA) is shifted to measure the importance or interest of the extracted regions. The experimental results show that the proposed method is effective to reduce over-segmentation in auto-extracting ROIs and performs well for different objects.
Keywords :
feature extraction; image segmentation; focus of attention; regions of interest extraction; visual attention; watershed segmentation; Chaos; Data mining; Digital images; Focusing; Image retrieval; Image segmentation; Information processing; Neural networks; Object detection; Signal processing; FOA; ROIs; Visual Attention Model; Watershed Segmentation;
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
DOI :
10.1109/ICNNSP.2008.4590375