A New Kernel-Based Neural Network for Sea Target Detection

摘要：

Sea target detection is an important goal for military purposes and navigation. Environmental noise and sea clutter are two major problems in sea target detection. A new novel Neural Network in Kernel Space (NNKS) is presented for classification of the target and non-target in color images, and it is followed with a new kernel neuron sea target detection system (KNNS) which is efficient especially in the critical color images with clutter, noise and complex background that relative methods are not effective. The neural network is trained with color characteristics of the target and non-target from the HSV color space.

关键词： Supervised learning Color segmentation Kernel-based neural network Sea target detection Noisy image detection.

作者: Ali Khayati Saeed Mirghasemi

作者单位: Co mputer and IT Department Islamic Azad University Parand branch Tehran, Iran Computer and IT Department Islamic Azad University Parand branch Tehran, Iran

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Industrial Electronics(2011年信息与工业电子国际会议 ICIIE 2011)

会议地点: 成都

会议语种:英文

页码: 140-144

在线出版日期: 2011-01-14（万方平台首次上网日期，不代表论文的发表时间）