为了实现苹果分级完全自动化，研究了苹果表面缺陷图像分类方法。
To realize apple automatic grading completely, the method for classifying apple surface defect by digital image processing was researched.
为了解决木材的分级问题，提出了利用神经网络和木材表面颜色特征对木材进行分级的方法。
In order to solve the problem of grading the timber, the authors have put forward a kind of classification method by utilizing neural network and wood surface color characteristics.
葡萄干大小不一，表面情况复杂，单纯依靠颜色特征或用肉眼判断，均达不到较好的分级效果。
The raisin has different size and complicated surface, so it couldn't be graded well only by color and naked eyes.
应用计算机视觉研究了绿橙表面缺陷的分级检测技术。
The grade identification technology of surface defects of green orange based on computer vision was studied.
提出了一种基于机器视觉技术的苹果表面纹理检测分级方法。
A detection and classification technique for the apple surface texture based on the machine vision was proposed.
为了实现快速自动分级，根据人类视觉特性，提出了一种基于均匀颜色空间的表面颜色分级方法。
In order to implement grading quickly, accurately and automatically, a color grading method based on perceptually uniform color space is put forward according to human vision system characteristics.
通过对损伤阈值分布曲线研究，可以有效地对缺陷进行分级判断，从而分析光学元件表面功能性缺陷的分布状况。
According to the damage threshold evolutions, the defects can be effectively classified and judged, and the distribution properties of functional defects in the optics surfaces can be analyzed.
方法：通过分别对于35例口腔鳞状细胞癌表面区、中心区、深层浸润区进行WHO病理分级，观察、评估不同区域的病理学分级是否存在差异。
Methods: Surface, center deep infiltration part of 35 OSCC cases were graded respectively (WHO grading1971). To observe where there were differences of pathological grading between these parts.
以方解石、大理石经超细粉碎、分级得到系列不同细度的重质碳酸钙，再经表面处理制得重质活性碳酸钙。
Calcite or marble is crushed, graded, and surface treated to be all kinds of technical natural calcium carbonate with different fineness. It is widely used in rubber, plastic, paint, and paper.
基于计算机视觉的水果自动分级指标主要是水果的大小、形状、颜色和表面缺陷。
Computer vision and image-processing techniques have been found increasingly useful for the fruit automatic quality inspection and defect sorting operation.
基于计算机视觉的水果自动分级指标主要是水果的大小、形状、颜色和表面缺陷。
Computer vision and image-processing techniques have been found increasingly useful for the fruit automatic quality inspection and defect sorting operation.
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