基于特征向量技术的飞机识别系统

A. Somaie, A. Badr, T. Salah
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引用次数: 6

摘要

飞机识别系统的一般任务是选择重要的方面,忽略无关的数据。飞机在图像平面内的周长具有足够的识别信息。使用形态学模块提取每个飞机的轮廓,并在灰度级对周长进行标准化。利用特征向量技术将输入图像对准固定方向。主成分分析用于为物体表示创建一个新的坐标系,其中每个飞机被投影到该平面上,投影系数用于识别目的。新特性不受平移、缩放和旋转的影响。对该算法进行了测试,发现仅使用x- 1个特征(其中x为参考飞机的编号)识别性能为100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aircraft recognition system using eigenvector technique
The general task of the aircraft identification system is to select the important aspects and ignore the irrelevant data. The perimeter of the aircraft in the image plane possesses sufficient information for recognition. The contour of each aircraft was extracted using a morphological module and the perimeter was standardised in the gray level. The eigenvector technique was exploited to align the input image to a fixed orientation. The principal component analysis is used to create a new co-ordinate system for object representation where each aircraft is projected onto that plane and the projection coefficients are used for the purpose of recognition. The new features are invariant to translation, scale and rotation. The presented algorithm was tested and it was found that the recognition performance is 100% using only an x-l features where x is the number of the referenced aircraft.
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