1996 年 58 巻 Supplement 号 p. 483-487
A neuro-net based hybrid image processing system which automatically recognizes lean tissues from the beef cut surface image and generates the lean tissue contour has been developed Because of the inhomogeneous distribution and fuzzy pattern of fat and lean tissues on the beef cut, conventional image segmentation and contour generation algorithms suffer from the heavy computing, algorithm complexness and even the poor robustness. The proposed system utilizes an artificial neural network to enhance the robustness of processing. The system is composed of three procedures such as pre-network, network based lean tissue segmentation and post-network procedure. At the pre-network stage, gray level images of beef cuts were segemented and resized appropriate to the network inputs. At the network stage, the normalized gray value of each grid image was taken as the network input. Pre-trained network generated the grid image output of the isolated lean tissue. A sequence of post-network processing was followed to obtain the detailed contour of the lean tissue. Training scheme of the network and separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex, fuzzy and irregular image.
