Underwater multi-source acoustic image feature extraction method and system

Abstract

The invention discloses an underwater multi-source acoustic feature extraction method and system. The method comprises the following steps: extracting geomorphic characteristic quantity of a water bottom geomorphic image, topographic characteristic quantity of a water bottom topographic image and stratum characteristic quantity of a water bottom stratum image, wherein the topographic characteristic quantity comprises a water bottom slope, a water bottom slope direction, a water bottom surface curvature and fractal dimension characteristics of a water bottom earth surface, the stratum characteristic quantity comprises an interface line characteristic quantity, an interface layer characteristic quantity and a surface section characteristic quantity, the interface line characteristic quantityrepresents the complexity of a water body substrate interface line, the interface layer characteristic quantity is a gray average value of the water body substrate interface layer, and the surface profile characteristic quantity comprises a gray scale statistical characteristic of the surface profile and a vertical texture characteristic of the surface profile; and determining the geomorphological characteristic quantity, the topographic characteristic quantity and the stratum characteristic quantity as a multi-source acoustic characteristic set. According to the invention, the extraction ofmulti-source acoustic features is realized, complementation of geomorphic, topographic and stratigraphic feature quantities is formed, the feature extraction is more comprehensive, and the classification precision is high when the method is used for subsequent sediment classification.

Description

technical field [0001] The invention relates to the field of underwater acoustic image analysis and processing, in particular to an underwater multi-source acoustic feature extraction method and system. Background technique [0002] Substrate classification refers to the classification of bottom materials (such as mud, sand, coarse sand, gravel, reef, etc.) of water bodies such as oceans, lakes, and rivers. Sediment classification is of great significance to scientific research, resource development, environmental protection and rights protection. Multi-source detection such as side-scan sonar, multi-beam sonar system and shallow strata profiler are common techniques for acoustic substrate classification. The main data obtained by these three types of acoustic equipment are multi-source acoustic images. Through the analysis of multi-source images And interpretation can realize the classification of substrate types. [0003] Representative multi-source acoustic images mainl...

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Problems solved by technology

[0004] At present, geomorphic images are usually used as the research object to achieve substrate classification, but the use of geomorphic image features can only describe the two-dimensional texture information of the underwater bottom, and the amount of information is very limited, and there are few feature extraction methods based on topographic images and stratigraphic profile images. Complementary with the extracted geomorphic features, it is not conducive to the application of sediment classification, resulting in low accuracy of existing sediment classification

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