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Theimagetextureanalyssbasedonthefractaldimension.r
- 图像纹理分析的源代码，基于分形维数的图像纹理分析-Image texture analysis of source code, based on fractal dimension of image texture analysis
fractal
- 计算图像的分形维数，盒子维。基于DBC（Differential Box-Counting）方法。结果表明，分形维数FD能够较好地刻画纹理图像的复杂程度。-Calculated image fractal dimension, box dimension. Based on DBC (Differential Box-Counting) method. The results show that the fractal dimension FD to better characterize th
image-texture-features
- 图像纹理特征提取，包括分形维数，灰度游程长度，灰度共生矩阵等五种图像纹理特征。-To extract image texture features, including fractal dimension, length of gray-level run-length, gray level co-occurrence matrix and other five kinds of image texture features。
Fractal-dimension-(FD)-calculation
- 采用盒计数法对三维表面进行分形维数分析，用分形维数表征物体表面纹理-The box counting method is used to analyze the fractal dimension of the three-dimensional surface, and the fractal dimension is used to characterize the surface texture of the object.
two
- ：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相