The Research Of Essence Recognition Method Based On Gray Level Co-occurrence Matrix Of Wood Digital Image

In this paper, applying digital image processing technology about China and abroad in the wood science and showinig development of different identification skills ,proposing a digital image recognition method based on wood gray-level co-occurrence matrix(GLCM) , discussed the feasibility of using wood gray to identify the species.Different wood species has different cell size, arrangement, more or less,ratio of cell wall are all different.By the influence of gray from different structure,aim at the feature of graly level co-occurrence matrix,This thesis extracted the wood texture features about cross section and tangential section, which including energy, entropy, moment of inertia, local stationarity,correlation(This texture feature and wood texure are two different concepts). Compared with the different texture feature. The parameters about gray-level co-occurrence matrix are discussed with 1 to 10 about the pixel distance.The results are when the bigger pixel distance,energy is lower,entropy is bigger,moment of inertia is bigger,local stationarity is bigger,correlation is lower. From the research of different pixel distance,find the pixel distance with a bigger difference among different species.The paper anlysised the variability of softwood and hardwood in texture feature, discussed the variability of different kinds of hardwood in texture feature,anlysising the distinction between different species,and established a 66 species gray feature database from it.In order to anlysis the influence of wood structure to texture parameter better,the paper analysised the distinction between earlywood and latewood by comparison.The paper analysis the ratio of cell wall,ratio of cell cavity ,ratio of cell wall to cavity based on binarization,and express the species distribution in different ratio of cell wall,ratio of cell wall to cavity.The ratio of cell wall of hardwood is relatively bigger by comparison.The paper discussed the correlation between cell wall ratio of cell cavity ,ratio of cell wall to cavity and texture parameters ,the result is the correlation is low,it shows the differences between using gray value to recognize and traditional using tissue structures to recognize.This paper proposed several methods about image recognition,from the discussion of texture feature of wood digital image,this paper used minimum difference method to identify. we extracted the parameters about the identified species,compared with the fetures on database,we can get the most similar species,it also output 3 sections about cross section,radial section and tangential section.The recognition interface gives the macroscopic and microscopic characteristics and some other basical information. The paper all used Visual C++ to achive in programme.The result is the method is feasible.