中文摘要：

利用木材图像的颜色、灰度、纹理等内容实现树种的相似性匹配检索，提取色调、饱和度、亮度、对比度、二阶角矩、方差和、长行程加重因子、分形维数、小波水平能量比重共9个特征参数，依据最大相似性数学原理，基于最小差值参数判别法和综合特征阈值法来检索样本。结果显示：基于图像纹理特征能够实现木材树种的检索和识别，综合特征阈值法的检索正确率与唯一性通常要好于最小差值判别法；但当被检索样本图像的纹理较弱或不呈现纹理特征时，检索结果的唯一性并不理想。综合而言，基于图像纹理特征最大相似性的木材树种检索识别较易实现，是一种值得继续发展和应用推广的木材树种识别方法。

英文摘要：

With the textural features of wood images as key bases, it aimed to realize the retrieval and identification of wood species. It adopted such contents as color, grey and texture of wood images, and measured with nine parameters： hue, saturation, illuminance, contrast, angular second moment, sum of variances, long run emphasis, fractal dimension, and wavelet horizontal energy proportion, then performed retrieval of wood species according to maximal similarity theory. The results showed that the retrieval and identification of wood species could be realized on bases of image textural features and relevant algorithms. The retrieval accuracy and uniqueness by limen discriminance of synthetical features were better than those by minimal differences method. But when the texture of samples was weak or textureless, the uniqueness of retrieval result would not be very satisfying. Even then, it is a worthwhile developing retrieval and identification method of wood species.