检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:蔡健荣[1] 周小军[1] 李玉良[1] 范军[1]
机构地区:[1]江苏大学食品与生物工程学院,镇江212013
出 处:《农业工程学报》2008年第1期175-178,共4页Transactions of the Chinese Society of Agricultural Engineering
基 金:国家863项目(2006AA10Z263);国家自然科学基金资助项目(30771243)
摘 要:采用2R-G-B色差分量,通过Ostu自适应阈值算法进行图像分割,利用形态运算消除分割后随机噪声,并对分割区域进行标记,利用区域面积和区域最小外接矩形长宽比参数进一步去除背景区域。对于多果重叠问题,利用T=Sqrt(S×I)形成新的图像提取边界,再结合形态学运算实现分割。最后利用优化的圆形Hough变换提取目标图像的形心坐标及半径,恢复遮挡果形。经验证有95%果实能正确识别。Using the image of 2R-G-B, Ostu algorithm was used to segment the images of mature oranges and background. Morphologic operation was used to remove the random noise and the object regions were labeled. According to the areas of the labeled regions and their ratios of the least rectangles' length and width, the remnant backgrounds were eliminated. For the overlapped fruits, a new image generated through formula T=Sqrt(S×I) and the boundary of the new image was extracted, with the additional morphologic operation, the overlapped fruits were separated. Finally, the optimized Circular Hough transform algorithm was used to extract centroid coordinates and radius, and then the fruit shape was recovered. The result shows that the correct recognition rate is up to 95%.
关 键 词:机器视觉 成熟柑橘 图像识别 特征提取 圆形Hough变换
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术] S666.2[自动化与计算机技术—计算机科学与技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.173