摘要： 为实现对X光图像中随机金属裂纹的自动识别，提出一种基于概率模型的裂纹自动识别算法。根据裂纹图像的特点建立理想概率模型，将其转换为理想模板，计算该模板与原始X光图像的Bhattacharyya系数矩阵，并将其映射为灰度图像。通过对该灰度图像二值化，并进行形态学操作，得到完整和精确的裂纹轮廓。仿真实验证明，该算法具有较强的自适应性和较高的识别精度。
关键词:
裂纹识别,
概率模型,
Bhattacharyya系数,
形态学,
二值化,
自适应
Abstract: In order to recognize the random crack in the X film image of the metal cast automated, this paper proposes a new algorithm to recognize the crack of metal. To realize the method, it constructs the ideal probability model according to the character of crack image and transform the model to the ideal template. It computes the Bhattacharyya coefficient between the ideal template and the original image in order to construct the Bhattacharyya coefficient matrix and transform the matrix to a grayscale image. The complete and accurate outline of the crack can be got by morphological operating. Experimental result shows the outcome of the algorithm is both adaptive and accurate.
Key words:
crack recognition,
probability model,
Bhattacharyya coefficient,
morphology,
binaryzation,
self-adaptive
中图分类号:
王彦, 谢晓方, 吴龙宝, 马钰, 朱宗健, 王丰. 基于概率模型的裂纹识别算法[J]. 计算机工程, 2012, 38(2): 189-191.
WANG Pan, XIE Xiao-Fang, TUN Long-Bao, MA Yu, SHU Zong-Jian, WANG Feng. Crack Recognition Algorithm Based on Probability Model[J]. Computer Engineering, 2012, 38(2): 189-191.