缺素叶片彩色图像颜色特征提取的研究

Extracting Color Features of Leaf Color Images

在提取无土栽培番茄营养元素亏缺叶片彩色图像的颜色特征时 ,为了使颜色特征有效性不受叶片大小、形状和叶片背景噪声影响 ,对由几种常用颜色系统表示的叶片图像进行了统计算法、相关系数算法提取叶片颜色特征的研究 ,以上的方法未能获得很有效的颜色特征。最后 ,提出了百分率直方图法提取缺素叶片图像颜色特征 ,进行了除去图像中白色背景影响的研究 ,用百分率直方图取代一般直方图以解决叶片大小对颜色特征提取影响的研究 ,以及如何确定提取颜色值区域的研究 ,此方法提取的颜色特征能理想地识别缺素番茄叶片 ,准确率在 70 %以上。

In this paper, several methods that were not influenced by shapes, sizes of leaves and image background noise were applied in extracting color features of tomato leaves that were short of a kind of nutrient. The methods included statistical algorithms, a algorithm of the correlation coefficient between two different color matrixes of the same leaf and the available ways of extracting color features by their histogram shapes. But these methods were not effective in extracting the color features of the tomato leaves. A new way of percent histogram was put forward. It includes the research of getting rid of the disturbance of the white background noise in the leaf image by drawing the histogram, and the research of removing the interference of leaf size by changing the histogram into percent histogram and the way of looking for the better color position in percent histogram for extracting effective color features. The experimental results of extracting color feature of the tomato leaves proved that the method was effective in separating different kinds of tomato leaves, and showed that the accuracy was above 70%.