Detection of Underwater Objects by Adaptive Threshold FCM Based on Frequency Domain and Time Domain

• 作者: Guangyu Liu Lin Li Shouxuan Jiang Xingmei Wang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: SONAR image Character frequency DOMAIN Block k-means CLUSTERING Fuzzy CLUSTERING algorithm Adaptive THRESHOLD
• 年，卷（期）: 2015,（1）
• 页码范围: 57-58
• 页数: 2页
• 分类号: C5

摘要

According to the characteristics of sonar image data with big data feature, In order to accurately detect underwater objects of sonar image, a novel adaptive threshold FCM (Fuzzy Clustering Algorithm, FCM) based on frequency domain and time domain is proposed. Based on the relationship between sonar image data and big data, Firstly, wavelet de-noising method is used to smooth noise. After de-noising, the sonar image is blocked and each sub-block region is processed by two-dimensional discrete Fourier transform, their maximum amplitude spectrum used as frequency domain character, then time domain of mean and standard deviation, frequency domain of maximum amplitude spectrum are taken for character to complete block k-means clustering, the initial clustering center is determined, after that made use of FCM on sonar image detection, based on clustered image, adaptive threshold is constructed by the distribution of sonar image sea-bottom reverberation region, and final detection results of sonar image are completed. The comparison different experiments demonstrate that the proposed algorithm get good detection precision and adaptability.