In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy ...In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy c means(FCM) algorithm. Through the attributes of size and shape pattern spectrum,the optimal morphological structuring element was determined.According to the optimal parameters,some image noises were removed with an improved area opening and closing by reconstruction operation,which consist of image regional markers,and the bubbles were finely separated from each other by watershed transform.The experimental results show that the structural element can be determined adaptively by shape and size pattern spectrum,and the froth image is segmented accurately.Compared with other froth image segmentation method,the proposed method achieves much high accuracy,based on which,the bubble size and shape features are extracted effectively.展开更多
Somatic cell counts （SCCs） levels indicate the occurrence of infections in goat udders and are related to the productivity of goat milk, cheese and yoghurt. This work presents a segmentation method for counting soma...Somatic cell counts （SCCs） levels indicate the occurrence of infections in goat udders and are related to the productivity of goat milk, cheese and yoghurt. This work presents a segmentation method for counting somatic cells in goat milk images, intending to detect an infection known as mastiffs, which is the major cause of loss in dairy farming. The image segmentation procedure is devised by using the lab color space and the watershed transform. A large number of samples under variable preparation conditions are treated with the proposed method. A comparison between manual and the proposed technique is presented. Promising results indicates that video-microscopy systems may be employed to develop automated SCC for goat milk.展开更多
基金Projects(60634020,60874069) supported by the National Natural Science Foundation of ChinaProject(2009AA04Z137) supported by the National High-Tech Research and Development Program of China
文摘In order to extract froth morphological feature,a bubble image adaptive segmentation method was proposed.Considering the image's low contrast and weak froth edges,froth image was coarsely segmented by using fuzzy c means(FCM) algorithm. Through the attributes of size and shape pattern spectrum,the optimal morphological structuring element was determined.According to the optimal parameters,some image noises were removed with an improved area opening and closing by reconstruction operation,which consist of image regional markers,and the bubbles were finely separated from each other by watershed transform.The experimental results show that the structural element can be determined adaptively by shape and size pattern spectrum,and the froth image is segmented accurately.Compared with other froth image segmentation method,the proposed method achieves much high accuracy,based on which,the bubble size and shape features are extracted effectively.
文摘Somatic cell counts （SCCs） levels indicate the occurrence of infections in goat udders and are related to the productivity of goat milk, cheese and yoghurt. This work presents a segmentation method for counting somatic cells in goat milk images, intending to detect an infection known as mastiffs, which is the major cause of loss in dairy farming. The image segmentation procedure is devised by using the lab color space and the watershed transform. A large number of samples under variable preparation conditions are treated with the proposed method. A comparison between manual and the proposed technique is presented. Promising results indicates that video-microscopy systems may be employed to develop automated SCC for goat milk.
