The Study of Side-Scan Sonar Image for Sea Bed Propreties

• Main Authors: Jhao-Ru Chen, 陳昭儒
• Other Authors: Gwo-Shyh Song
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/90347121871875566047

碩士 === 國立臺灣大學 === 海洋研究所 === 97 === In this study, side-scan signals were displayed as sonograph, and different morphological images were classified using digital image processing methods. The data of side-scan sonar image was collected in the project of “Disposal plan of the Keelung Harbor dredging material” in June and October 2007, respectively. Two kinds of method to analysis image are: Wavelet Packet Feature (WPF) and Gray Level Co-occurrence Matrix (GLCM). WPF constructs the signals into seven bands to calculate their respective statistics, and each morphological feature poses their represented trend of statistics among the bands; GLCM produces 16 by 16 grayscale matrix based on the grayscale value which is derived from the pairs of each of 8 peripheral elements matching with the central pixel, respectively, in a sequence of 3 by 3 matrix. GLCM matrix is to establish the characteristics or distribution for each specified image. In the follow, this study also tries to recognize texture composed by side-scan image using automatically identification method instead of manually approach, especially to identify some specific sediment properties. Results of morphological recognition using side-scan images show WPF distribution among the bands and GLCM entropy and homogeneity patterns provide successful differentiation on different morphological images. In addition, for automatic identification, this method can identify their respective locations for those specific sediment properties. In the final, the study brings up some discussions regarding to error judgment to the images resulted from data processing and data quality.