Title :
An automatic targets detection method from SAS images based on mean-standard deviation
Author :
Li, Changzhi ; Tian, Jie ; Zhang, Yangfan ; Huang, Haining ; Zhang, Chunhua
Author_Institution :
Inst. of Acoust., Chinese Acad. of Sci. Beijing, Beijing, China
Abstract :
Targets detection is important for the analysis of Synthetic Aperture Sonar (SAS) images. An automatic targets detection method from SAS images is presented by analyzing the statistical properties of the images. The method mainly has three procedures: preprocessing of SAS images, especially the mean-standard deviation segmentation method to binarize the images, extracting areas of connected components in the binary images as features, maximum area of connected components method detecting. At last, the targets detection method based on mean-standard deviation is applied to lake-trial datasets for validation.
Keywords :
feature extraction; image segmentation; object detection; sonar imaging; automatic targets detection method; binary images; feature extraction; lake-trial datasets; mean-standard deviation segmentation method; synthetic aperture sonar images; Entropy; Image segmentation; Lakes; Noise; Object detection; Pixel; Synthetic aperture sonar; mean-standard deviation; synthetic aperture sonar; targets detection;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5646809
