The Smart Technology Research Of Using Image Project And Frame Theory To Identify The Human Cells

Nowadays, the level understanding is the most difficult in image project. In this paper, we use statistics of pixel-based, combine image processing, image analysis with image understanding to process medical image. At the same time, it's retaining the original advantage of the algorithm, resolves all levels'isolation, and also reduces human intervention in the process of system operation. It's possible that automatic image analysis and understanding. This paper focuses on describes image processing, image analysis, image understanding combination process. Texture is an inherent characteristic of things, such as second moment, entropy, contrast, energy and related features as framework knowledge used for the artificial intelligence theory. Theoretical analysis is possible that texture features combined with the frame theory, and also gives detailed reasoning framework. The experimental results show that the above process, after image processing, image recognition can be effective.With the expansion of human activities, the researched subjects increasing, the image as a tremendous amount of information, vivid information carrier has been widely applied to all walks of life. In the medical field, by reading pieces of cell to determine the disease; in the large-scale population health survey has also important applications in the cell images. In order to reduce duplication of errors, improve automated image recognition is another purpose of this article. The statistical methods of image texture analysis, texture features can guarantee the stability. When the image enlargement, reduction, rotation, texture feature value changes is in a smaller range. Human intelligence reflected in past experience and the accumulation of knowledge, in order to the computer like human intelligence, we need to teach computer knowledge. Frame theory as a description of the structural things, the texture characteristics of cells can be converted to knowledge representation, reasoning with the basis of the framework, helping us to understand the images automatically.In the paper, through researching the process of image understanding, we explore the process for the identification of human cell technology. The texture image understanding technology with other technologies combined, can better improve the level of image recognition. System experiment using different human cells can effectively complete the cell recognition. System also uses the same image of the body parts to complete the image texture analysis, such as two the lung of images, because the same parts of the image, texture features should be similar, the experimental results are consistent with the expected result. This paper presents an effective way of image understanding, practice and theory in a certain reference value and significance.