Tongue inspection is one of the most important methods of Traditional Chinese Medicine diagnoses. Traditional tongue inspection mainly depends on observations to tongue substance, tongue coating and tongue pattern and diagnostic experience of the doctors. Diagnostic results are restricted by doctor's knowledge level, their experience as well as other subjective factors and affected by the light and temperature of external environment. In order to solve this problem, we should combine Traditional Chinese Medicine experts' diagnostic experience with modern information technologies, check and analyze tongues quantitively and objectively, and make scientific diagnoses. However, to realize quantitive and objective tongue checks and analyses, extracting tongue from the mouth and face is the first important step. A novel approach for tongue image extraction is proposed to solve this problem in this article. It utilizes greedy rules to combine color information and space information to search object tongue area in the 2-dimensional sample space, and the start position of the search, intensity threshold and hue threshold are selected fully automatically. Comparison experiment results indicate that this method can extract tongue from the raw image effectively and we have made a breakthrough in extracting the tongues with thick coating. Moreover, the tongue images extracted by this method can be used as valid bases for the later quantitive analyses.
Tongue image with coating is of important clinical diagnostic meaning, but traditional tongue image extraction method is not competent for extraction of tongue image with thick coating. In this paper, a novel method is suggested, which applies multiobjective greedy rules and makes fusion of color and space information in order to extract tongue image accurately. A comparative study of several contemporary tongue image extraction methods is also made from the aspects of accuracy and efficiency. As the experimental results show, geodesic active contour is quite slow and not accurate, the other 3 methods achieve fairly good segmentation results except in the case of the tongue with thick coating, our method achieves ideal segmentation results whatever types of tongue images are, and efficiency of our method is acceptable for the application of quantitative check of tongue image.
A new approach to modelling roles in manufacturing organisations is described. Many companies seek to manufacture a variety of products with common resources. Hence complex decision making is required when seeking to match suitable human and technical resource systems to processes and workflows. The new approach uses Enterprise Modelling to explicitly define functional and flexibility competencies that must be possessed by suitable role holders. Also described is how Causal loop modelling can be used to reason about dependencies between different role attributes. The approach is targeted at the design and application of simulation models that enable relative performance comparisons (such as work throughout, lead-time and process costs) to be made and to show how performance is affected by different role decompositions and resourcing policies. The approach is illustrated with reference to a case study furniture making company.
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