基于HSI颜色空间与灰度波动相结合的复杂桥梁蜂窝麻面的图像分割

doi:10.11772/j.issn.1001-9081.2018081688

计算机应用 ›› 2019, Vol. 39 ›› Issue (3): 882-887.DOI: 10.11772/j.issn.1001-9081.2018081688

• 虚拟现实与多媒体计算 • 上一篇下一篇

基于HSI颜色空间与灰度波动相结合的复杂桥梁蜂窝麻面的图像分割

姚学练¹, 贺福强¹, 平安¹, 罗红¹, 万思路²

1. 贵州大学机械工程学院, 贵阳 550025;
2. 贵州省交通科学研究院股份有限公司, 贵阳 550025

收稿日期:2018-08-15 修回日期:2018-10-25 出版日期:2019-03-10 发布日期:2019-03-11
通讯作者: 贺福强
作者简介:姚学练(1994-),男,贵州荔波人,硕士研究生,主要研究方向:机器视觉检测、模式识别;贺福强(1975-),男,贵州遵义人,副教授,博士,主要研究方向:机器视觉检测、模式识别;平安(1994-),男,江西抚州人,硕士研究生,主要研究方向:机器视觉检测、模式识别;罗红(1994-),男,贵州遵义人,硕士研究生,主要研究方向:机器视觉检测、模式识别;万思路(1990-),男,贵州遵义人,硕士,主要研究方向:建筑与土木工程。
基金资助:
贵州省交通科学研究院股份有限公司科技项目（GZJKY科技字2017-20）。

Image segmentation for complex voids and pits of bridge based on combination of HSI color space and gray fluctuation

YAO Xuelian¹, HE Fuqiang¹, PING An¹, LUO Hong¹, WAN Silu²

1. College of Mechanical Engineering, Guizhou University, Guiyang Guizhou 550025, China;
2. Guizhou Transport Science Research Institute Company Limited, Guiyang Guizhou 550025, China

Received:2018-08-15 Revised:2018-10-25 Online:2019-03-10 Published:2019-03-11
Supported by:
This work is partially supported by the Science and Technology Project of Guizhou Provincial Transportation Science Research Institute Company Limited (GZJKY2017-20).

摘要/Abstract

摘要：

针对桥梁蜂窝麻面图像经常存在光照不均、多背景并存的干扰问题，提出了基于HSI颜色空间与灰度波动相结合的复杂桥梁蜂窝麻面的图像分割算法。首先，绘制S分量灰度变化曲线；其次，搜索曲线所有潜在的波峰波谷，并求相邻波峰波谷的高度差；然后，基于灰度像素个数差分值的标准差筛选出部分高度差；最后，基于部分高度差的标准差搜索最佳阈值完成图像的阈值分割。实验结果表明，与二维OTSU法、Niblack法、二维Tsallis熵法等几种算法相比，该算法的分割效果和实时性更好。

关键词: 彩色图像, HSI空间, 灰度波动, 高度差, 标准差, 图像分割

Abstract:

As the voids and pits image of bridge often has uneven illumination and multi-background interference problems, an image segmentation algorithm for complex voids and pits of bridge was proposed based on HSI color space and gray fluctuation. Firstly, S-component gray curve was plotted and all the potential peaks and troughs of the curve were searched, then the height differences between adjacent peaks and thoughs were calculated. Secondly, partial height differences were selected based on the standard deviation of gray pixel difference value. Finally the threshold segmentation of image was finished by searching the best threshold based on the standard deviation of partial height differences. Experimental results show that the proposed algorithm has better segmentation effect and real-time performance than OTSU, Niblack and Tsallis entropy method.

Key words: color image, HSI space, gray fluctuation, height difference, standard deviation, image segmentation

中图分类号:

TP391.4

姚学练, 贺福强, 平安, 罗红, 万思路. 基于HSI颜色空间与灰度波动相结合的复杂桥梁蜂窝麻面的图像分割[J]. 计算机应用, 2019, 39(3): 882-887.

YAO Xuelian, HE Fuqiang, PING An, LUO Hong, WAN Silu. Image segmentation for complex voids and pits of bridge based on combination of HSI color space and gray fluctuation[J]. Journal of Computer Applications, 2019, 39(3): 882-887.

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基于HSI颜色空间与灰度波动相结合的复杂桥梁蜂窝麻面的图像分割

Image segmentation for complex voids and pits of bridge based on combination of HSI color space and gray fluctuation

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