摘要
对含有复杂背景的彩色柑桔图像应用多元统计中的马氏距离分析法分别进行了图像分割和目标识别,对识别结果进行了分析,计算了不同条件下拍摄的柑桔图像中柑桔所占的面积比例。结果表明,马氏距离法在合理选择图像元素类别和各类别判定指标的情况下,经过对进行训练的样本空间进行确认,能够克服光照、复杂背景等因素的影响,较好地对柑桔彩色图像进行了图像分割,通过程序实现了目标面积比例的计算。
Orange color pictures with complicated background were divided and the objects in them were detected purposely by using the Mahalanobis distance algorithm which belongs to multi-element statistical analysis and the results were analyzed. The ratio of orange fruits in the pictures of different growing period was calculated. It indicated that the Mahalanobis distance algorithm could overcome the influences of the light and the complicated background, as long as the elements of the picture and its index were reasonably selected and confirmed. The results showed that by programming, it could divide the image and detect the objects effectively.
出处
《中山大学学报（自然科学版）》
CAS
CSCD
北大核心
2005年第A02期136-140,共5页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
国家自然科学基金项目资助(30270764)
关键词
柑桔图像
马氏距离
图像分割
目标识别
误差分析
orange pictures
Mahanalobis distance
image clustering
object detection
error analysis
