基于劳伦茨信息值的水下大坝裂缝提取算法

针对水下图像光照不均衡、对比度低、模糊不清以及噪声严重的问题，提出一种新的基于劳伦茨信息值的水下大坝裂缝检测算法。首先根据劳伦茨信息值去除不含有裂缝信息的图像块，接着提取连通域的圆形度、面积特征，采用k均值聚类算法，提取最终的裂缝区域。实验结果证明，本文算法能够在复杂的水下环境中准确、高效地提取大坝表面裂缝。

A Novel Underwater Dam Crack Extraction Algorithm Based on Lorentz Information Measure

Because underwater images generally have many problems, such as uneven illumination, low contrast, blurring and much noise, a novel underwater dam crack extraction algorithm based on Lorentz Information Measure is proposed to deal with the problems. First, the image blocks without crack information are removed according to Lorentz Information Measure. Second, features of connected domains, i.e., circularity and area, are extracted. Then k-means clustering method is used to achieve final cracks by 2-D feature space. The experimental results show that the proposed algorithm can extract cracks from underwater dam images precisely and effectively.