摘要
针对海天背景下彩色近景舰船图像,采用了一种基于多尺度特征簇的舰船目标快速定位与识别方法,此方法对旋转具有鲁棒性,对光照具有良好的适应性。借鉴Canny边缘检测与图像金子塔及最小生成树聚类算法的思想,设计了一套可适应目标多尺度特性并提高Canny边缘检测自适应性的"特征簇"目标定位算法,结合概率树分类器与二维主成分分析算法,可对多视角、多目标类型舰船目标进行识别,并根据全概率公式评估识别结果。
This paper approaches the problem of detecting and recognizing ship targets in color images based on sea-sky background.We propose a method based on multi-scale feature cluster robust to the changes in scale,orientation and illumination of the image and can fast detect and recognize ship targets.For ship detection,a＂group feature＂detecting method that can adapt to the multi-scale of the target and improve the adaptive of the canny edge detection is proposed that combines the canny edge detection algorithm,image pyramid algorithm and minimum spanning tree clustering algorithm.For ship recognition,a＂probability tree＂recognition method that can recognize a ship target in multi-angle,multi-target approach is proposed,combining with the probability tree classifier and principal component analysis algorithm.The recognition results are calculated by the total probability formula.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2016年第1期111-116,共6页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(41271454)~~
关键词
舰船目标检测
目标定位与识别
彩色图像处理
ship target detection
object detection and recognition
color image processing
