基于欧氏距离的实时直线检测算法

提出一种新的直线检测算法。与已有算法不同，该算法并非通过坐标系的转换，而是基于将离散曲线各点前后k个点对间欧氏距离平方和定义为该点的直线度，并推导出直线段上除首尾有限个点外其余各点直线度最大这一性质。利用该性质，该算法首先运用Freeman链码的性质选择出物体边界上明显属于直线的像素，然后在剩余的边界点中通过计算并寻找连续直线度最大的点而定位出直线。实验结果表明，该算法具有较高的稳定性、实时性和准确性。

Line detection based on Euclidean distance

To detect lines in digital image, this paper proposed a new algorithm. Different form traditional line detection algorithms, the algorithm does not search another coordinate transformation, but defines the line degree of a point in a curve as the sum of k Euclidean distance square between points centered at the point, and deduces that except limited points in the head and tail, points in a line segment will have the maximum line degree. Derived from this characteristic, the new algorithm detects line segments in a two-pass manner. Firstly, the points on a curve that obviously belonged to a line segment were selected by using Freeman chain-code. Secondly, the points that were continuous and had the maximum line degree were selected. The result shows the algorithm is stable, precise and fast.