计算机科学 ›› 2018, Vol. 45 ›› Issue (9): 279-282.doi: 10.11896/j.issn.1002-137X.2018.09.046

• 图形图像与模式识别 • 上一篇    下一篇

基于随机区域合并的自动彩色图像分割算法

辜卫东1, 李兵2   

  1. 湖北大学计算机与信息工程学院 武汉4300721
    武汉大学国际软件学院 武汉4300722
  • 收稿日期:2017-07-05 出版日期:2018-09-20 发布日期:2018-10-10
  • 通讯作者: 辜卫东(1968-),男,实验师,主要研究方向为计算机应用、图像处理等,E-mail:gwd0915@163.com
  • 作者简介:李 兵(1967-),男,教授,博士生导师,主要研究方向为算法设计等。
  • 基金资助:
    本文受国家重点研发计划(2016YFB0800401),国家重点基础研究发展计划(2014CB340401),国家自然科学基金(61572371),武汉市黄鹤英才(专项)计划资助。

Automatic Color Image Segmentation Algorithm Based on Random Region Merging

GU Wei-dong1, LI Bing2   

  1. School of Computer and Information Engineering,Hubei University,Wuhan 430072,China1
    International School of Software,Wuhan University,Wuhan 430072,China2
  • Received:2017-07-05 Online:2018-09-20 Published:2018-10-10

摘要: 针对彩色图像分割精度不高的问题,提出了一种具备多尺度空间约束的自动彩色图像分割算法。基于改进的随机区域合并方法,该算法首先实施双边分解并执行基于多通道信息和多尺度梯度的过度分割;然后,在CIE L*a*b*颜色空间中使用规范化的颜色直方图来表示每个子区域,构造一个基于过度分割结果的区域邻接图;最后,在区域邻接图上执行具备空间约束条件的随机区域合并策略,为每个尺度构造一张分割图。在BSDS图像数据库中进行对比实验,结果表明,在直接视觉对比和量化分析上,相比现有的分割算法,所提方法表现出了更好的分割效果。

关键词: 彩色图像分割, 目标检测, 随机区域合并, 图像处理

Abstract: In order to solve the problem of low segmentation accuracy for color image,a new algorithm for automatically segmenting color image with multi-scale spatial constraints was proposed.Based on the improved random region merging method,this algorithm firstly implements the bilateral decomposition and performs the over segmentation based on the multi-channel information and the multi-scale gradient.Then,in the CIE L*a*b* color space,a normalized color histogram is adopted to represent each sub-region.Finally,a stochastic region merging strategy with spatial constraints is constructed on the region adjacency graph to construct a segmentation graph for each scale.The experimental results in BSDS image database demonstrate that the proposed method has better segmentation performance than existing algorithms.

Key words: Color image segmentation, Image processing, Object detection, Random region merging

中图分类号: 

  • TP391.41
[1] WU D,HU S,HU L Z,et al.FSVM color image segmentation based on visual attention and improved membership[J].Application of Computer System,2017,24(1):1123-1134.(in Chinese)
吴迪,胡胜,胡灵芝,等.基于视觉注意和改进隶属度的FSVM彩色图像分割[J].计算机系统应用,2017,24(1):1123-1134.
[2]PENG J,ZHOU X Z,LEI Y J.Color image segmentation based on prior color covariance constraint[J].Computer Engineering,2017,43(4):251-256.(in Chinese)
彭浩,周新志,雷印杰.基于先验色彩协方差约束的彩色图像分割[J].计算机工程,2017,43(4):251-256.
[3]LENG J W,SHEN F T.Hydrological image segmentation based on HSV color model and regional growth method[J].Computer Engineering,2017,43(7):223-228.(in Chinese)
冷建伟,沈芳婷.基于HSV色彩模型与区域生长法的水文图像分割[J].计算机工程,2017,43(7):223-228.
[4]CHEN K,CHEN F,DAI M,et al.Two-dimensional entropy
multi-threshold image segmentation based on firefly algorithm [J].Optical Precision Engineering,2014,22(2):517-523.(in Chinese)
陈恺,陈芳,戴敏,等.基于萤火虫算法的二维熵多阈值快速图像分割[J].光学精密工程,2014,22(2):517-523.
[5]SZCZYPI,SKI P,KLEPACZKO A,et al.Texture and color
based image segmentation and pathology detection in capsule endoscopy videos[J].Computer Methods & Programs in Biomedicine,2014,113(1):396-411.
[6]KHAN A,ULLAH J,JAFFAR M A,et al.Color image segmentation:a novel spatial fuzzy genetic algorithm[J].Signal,Image and Video Processing,2014,8(7):1233-1243.
[7]WONG A,SCHARCANSKI J,FIEGUTH P.Automatic skin lesion segmentation via iterative stochastic region merging[J].IEEE Transactions on Information Technology in Biomedicine A Publication of the IEEE Engineering in Medicine & Biology Society,2011,15(6):929-936.
[8]BORA D J,GUPTA A K.A New Efficient Color Image Segmentation Approach Based on Combination of Histogram Equa-lization with Watershed Algorithm[J].International Journal of Computer & Engineering,2016,4(6):156-167.
[9]RAJABY E,AHADI S M,AGHAEINIA H.Robust color image segmentation using fuzzy c-means with weighted hue and intensity[J].Digital Signal Processing,2016,51(7):170-183.
[10]ZHOU C,WU D,QIN W,et al.An efficient two-stage region
merging method for interactive image segmentation[J].Compu-ters & Electrical Engineering,2016,54(15):220-229.
[11]VASQUEZ D,SCHARCANSKI J,WONG A,et al.A novel 3D approach for the extraction of the wetting front in CT images of soil profiles[C]∥Instrumentation and Measurement Technology Conference.IEEE,2013:1540-1543.
[12]JYOTIBORA D,GUPTA A K.A New Approach towards Clustering based Color Image Segmentation[J].International Journal of Computer Applications,2014,107(12):23-30.
[13]SAGˇ T,CUNKAS M.Color image segmentation basedon multiobjective artificial bee colony optimization[J].Applied Soft Computing,2015,34(C):389-401.
[14]SUN H J,DENG T Q,LI Y C.Improved watershed image segmentation algorithm [J].Journal of Harbin Engineering University,2014,35(7):857-864.(in Chinese)
孙惠杰,邓廷权,李艳超.改进的分水岭图像分割算法[J].哈尔滨工程大学学报,2014,35(7):857-864.
[1] 刘冬梅, 徐洋, 吴泽彬, 刘倩, 宋斌, 韦志辉.
基于边框距离度量的增量目标检测方法
Incremental Object Detection Method Based on Border Distance Measurement
计算机科学, 2022, 49(8): 136-142. https://doi.org/10.11896/jsjkx.220100132
[2] 王灿, 刘永坚, 解庆, 马艳春.
基于软标签和样本权重优化的Anchor Free目标检测算法
Anchor Free Object Detection Algorithm Based on Soft Label and Sample Weight Optimization
计算机科学, 2022, 49(8): 157-164. https://doi.org/10.11896/jsjkx.210600240
[3] 郭拯危, 付泽文, 李宁, 白澜.
高分辨率斜视聚束SAR回波仿真加速算法研究
Study on Acceleration Algorithm for Raw Data Simulation of High Resolution Squint Spotlight SAR
计算机科学, 2022, 49(8): 178-183. https://doi.org/10.11896/jsjkx.210600066
[4] 祝文韬, 兰先超, 罗唤霖, 岳彬, 汪洋.
改进Faster R-CNN的光学遥感飞机目标检测
Remote Sensing Aircraft Target Detection Based on Improved Faster R-CNN
计算机科学, 2022, 49(6A): 378-383. https://doi.org/10.11896/jsjkx.210300121
[5] 马宾, 付永康, 王春鹏, 李健, 王玉立.
基于GDIoU损失函数的YOLOv4绝缘子高效定位算法
High Performance Insulators Location Scheme Based on YOLOv4 with GDIoU Loss Function
计算机科学, 2022, 49(6A): 412-417. https://doi.org/10.11896/jsjkx.210600089
[6] 陈永平, 朱建清, 谢懿, 吴含笑, 曾焕强.
基于外接圆半径差损失的实时安全帽检测算法
Real-time Helmet Detection Algorithm Based on Circumcircle Radius Difference Loss
计算机科学, 2022, 49(6A): 424-428. https://doi.org/10.11896/jsjkx.220100252
[7] 刘伟业, 鲁慧民, 李玉鹏, 马宁.
指静脉识别技术研究综述
Survey on Finger Vein Recognition Research
计算机科学, 2022, 49(6A): 1-11. https://doi.org/10.11896/jsjkx.210400056
[8] 来腾飞, 周海洋, 余飞鸿.
视频流的实时景深延拓算法
Real-time Extend Depth of Field Algorithm for Video Processing
计算机科学, 2022, 49(6A): 314-318. https://doi.org/10.11896/jsjkx.201100187
[9] 陈佳舟, 赵熠波, 徐阳辉, 马骥, 金灵枫, 秦绪佳.
三维城市场景中的小物体检测
Small Object Detection in 3D Urban Scenes
计算机科学, 2022, 49(6): 238-244. https://doi.org/10.11896/jsjkx.210400174
[10] 胡伏原, 万新军, 沈鸣飞, 徐江浪, 姚睿, 陶重犇.
深度卷积神经网络图像实例分割方法研究进展
Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network
计算机科学, 2022, 49(5): 10-24. https://doi.org/10.11896/jsjkx.210200038
[11] 徐涛, 陈奕仁, 吕宗磊.
基于改进YOLOv3的机坪工作人员反光背心检测研究
Study on Reflective Vest Detection for Apron Workers Based on Improved YOLOv3 Algorithm
计算机科学, 2022, 49(4): 239-246. https://doi.org/10.11896/jsjkx.210200119
[12] 张侣, 周博文, 吴亮红.
基于改进卷积注意力模块与残差结构的SSD网络
SSD Network Based on Improved Convolutional Attention Module and Residual Structure
计算机科学, 2022, 49(3): 211-217. https://doi.org/10.11896/jsjkx.201200019
[13] 赫晓慧, 邱芳冰, 程淅杰, 田智慧, 周广胜.
基于边缘特征融合的高分影像建筑物目标检测
High-resolution Image Building Target Detection Based on Edge Feature Fusion
计算机科学, 2021, 48(9): 140-145. https://doi.org/10.11896/jsjkx.200800002
[14] 袁磊, 刘紫燕, 朱明成, 马珊珊, 陈霖周廷.
融合改进密集连接和分布排序损失的遥感图像检测
Improved YOLOv3 Remote Sensing Target Detection Based on Improved Dense Connection and Distributional Ranking Loss
计算机科学, 2021, 48(9): 168-173. https://doi.org/10.11896/jsjkx.200800001
[15] 龚浩田, 张萌.
基于关键点检测的无锚框轻量级目标检测算法
Lightweight Anchor-free Object Detection Algorithm Based on Keypoint Detection
计算机科学, 2021, 48(8): 106-110. https://doi.org/10.11896/jsjkx.200700161
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!