焦安波, 邵立云, 李晨曦, 马俊凯, 王学娟, 罗海波. 基于直线组仿射不变特征的自动目标识别算法[J]. 红外与激光工程, 2019, 48(S2): 142-148. DOI: 10.3788/IRLA201948.S226003
引用本文: 焦安波, 邵立云, 李晨曦, 马俊凯, 王学娟, 罗海波. 基于直线组仿射不变特征的自动目标识别算法[J]. 红外与激光工程, 2019, 48(S2): 142-148. DOI: 10.3788/IRLA201948.S226003
Jiao Anbo, Shao Liyun, Li Chenxi, Ma Junkai, Wang Xuejuan, Luo Haibo. Automatic target recognition algorithm based on affine invariant feature of line grouping[J]. Infrared and Laser Engineering, 2019, 48(S2): 142-148. DOI: 10.3788/IRLA201948.S226003
Citation: Jiao Anbo, Shao Liyun, Li Chenxi, Ma Junkai, Wang Xuejuan, Luo Haibo. Automatic target recognition algorithm based on affine invariant feature of line grouping[J]. Infrared and Laser Engineering, 2019, 48(S2): 142-148. DOI: 10.3788/IRLA201948.S226003

基于直线组仿射不变特征的自动目标识别算法

Automatic target recognition algorithm based on affine invariant feature of line grouping

  • 摘要: 为了提高基于异源模板匹配的自动目标识别方法的精度和准确率,提出了一种采用直线组几何基元的图像匹配算法,该算法利用直线组表示目标,利用直线组中各条直线构成的三角形面积之比作为描述直线组的特征量,在所有候选直线组中找到与目标匹配的最佳直线组,并确定组内直线的一一对应关系,求出模板图与实时图中的同名点,最后利用同名点检测出实时图中目标的位置;此外,还提出了一种在实时图中进行直线提纯的方法。该方法可以提出实时图中的主要直线,为文中所提算法的精确性提供了保障。实验结果表明:文中提出方法具有较高的匹配精度和准确率。

     

    Abstract: In order to improve the accuracy of the multi-sensor automatic target recognition algorithm,based on line group matching, an image matching algorithm using linear group geometric primitives was proposed. Line group was used to represent the target. Every three lines in line group can compose a triangle. An affine invariant, which consisted of the ratio of these triangles' area, was considered as a distinct feature to describe the line group. The best matching line group was found among the candidate line groups in real-time infrared image. The corresponding points between target and real-time image can be obtained through the matching lines. Then the location of the target can be computed through affine transformation. Finally, the position of the target in the real-time map was detected by the same-named point; in addition, a method of linear purification in the real-time infrared image was proposed. The extracted primary lines provided a condition which ensured the effectiveness and efficiency of the proposed recognition algorithm. Experimental result shows that the proposed algorithm has a high matching accuracy in multi-sensor target recognition.

     

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