摘要
【目的】将研究对象紫色土自然断面图像从复杂背景中分割出来,以消除复杂背景的影响,为对紫色土视觉图像进一步分析处理、识别打下基础。【方法】通过对紫色土自然断面图像统计分析,证明它的H域有良好的聚集特征,且在95%和97%置信点近似于正态分布;因此,根据正态分布确定紫色土壤自然断面的H阈值,分割紫色土壤自然断面图像。【结果】用获得的二值分割图像与原图像计算哈达玛积,分割提取出了完整的紫色土自然断面区域图像。【结论】算法分析及仿真实验显示:相对于对比算法,新的算法分割速度更快,分割提取出的紫色土自然断面图像更完整;该算法有效。
[Purposes]The first job is to separate out the natural cross-section image of purple soil from the chaotic background in lhe purple soil images because it is a base of the processing in future.[Methods]It displays the clustering property which is palpable in the H values of the HSV color space to study the natural cross-section image of purple soil.The distribution of the pixel number in the H values is closer to a normal distribution at the points that confidence level is 95%or 97%.So it is feasible to compute the H threshold with the normal distribution and to separate out the natural cross-section image of purple soil with it.[Findings]The segmcn tation image of the purple soil is obtai ned by calculating the Hadamard prod net with the bin ary image that elim in ates the discrete small and small holes and the original image.[Conclusions]Theoretical analysis and simulation experiments show that the algorithm is effective,and its computing speed is faster and it improves the image segmentation effect compared with the contrast algorithms.
作者
程蓉
曾绍华
罗俣桐
付登伟
王帅
杨圣明
CHENG Rong;ZENG Shaohua;LUO Yutong;FU Dengwei;WANG Shuai;YANG Shengming(College of Computer and In formation *Science Chongqing Normal University,Chongqing 401331;The Engineering & Technology Research Center of Digital Agriculture Service,Chongqing 401331;The Center of Agriculture Technology Promotion,Nanchuan Chongqing,408400;The Master Station of Agricultural Technology Promotion,Chongqing 400121,China)
出处
《重庆师范大学学报(自然科学版)》
CAS
北大核心
2019年第2期84-93,共10页
Journal of Chongqing Normal University:Natural Science
基金
重庆市教育委员会科学技术研究项目(No.KJ1751484
No.KJ1500321)
重庆市研究生科研创新项目(No.CYS17185)
关键词
紫色土图像
彩色图像分割
H域阈值
purple soil image
color image segmentalion
H threshold