Modulus Maxima-based Features Extracted From Ultrasonic Seabed Sediment Classification Recognition

Along with land mineral resource used up, Oceanic cobalt crust resource has been a commercial foreground strategical resource in 21 century and the head developed countries in the world have been doing work of investigation and exploitation. In order to quicken the step of exploitation of seabed cobalt crust in our country, and imbursed by the national natural science fund item "Study on the Abyssalbenthic Cobalt-rich Crusts Tiny terrain Detecting Technology and the Best Collection Deepness Model", the investigation was done of the identification and classification of seabed sediment in the dissertation.A classification method was proposed based on the application of modulus maxima in feature extraction. Different echo is gained to detect different sediment. The jumping-off was found out making use of the correlation principle. Intercept echo. Then do wavelets transform and pick out the modulus maxima feature. They were compressed with optimal set of discriminant vectors. At the end, analysis was done in the classifier. Based on above-mentioned theory, according as the standard of nature sediment, 14 sediment was made of mud,sand and gravel according to different proportion. The modulus maxima feature is different corresponding different echo. A classification and identification model was found on experiments. In order to validate the model, we sampled sediment from the XiangJiang riverbed. The experiment was done to the samples. A portion of the samples were griddled and weighed. Compared the two results, the exactness identification rate was about 80 percents. Look from the results, this method and model are correct and reliable.The research affords favorable theoretic value for the identification and classification of seabed sediment. It also has realistic significance for the seabed physiognomy and characters. And the research furnishes effective technique sustain for the country abyssalbenthic mining.