【作者】 智川； 李志建； 石毅；

【Author】 ZHI Chuan 1, a , LI Zhijian 1, b and SHI Yi 2, c 1. Shaanxi University of Science and Technology, China 2. Shaanxi Hwatec Science & Technology Co. Ltd, China

【机构】 陕西科技大学； 陕西华拓科技有限责任公司；

【摘要】 设备彩色特征化的本质是设备相关颜色空间与设备无关颜色空间之间的相互转换。本文通过定义色度空间转换模型的鲁棒性的概念及其评价方法,对基于模糊控制的颜色空间转换方法,基于动态子空间划分的BP神经网络颜色空间转换方法和基于模糊神经辨识方法的颜色空间转换模型这几种人工智能的颜色空间转换方法的鲁棒性做了比较研究。研究结果显示基于模糊神经辨识方法的颜色空间转换模型能够结合BP神经网络和模糊控制的特点,从而使模型的鲁棒性得到很大的提高。更多还原

【Abstract】 The nature of device color characteristic methods is the mutual conversion of device-dependent color space and device-independent color space. This paper does the comparative study on the robustness of some color space conversion methods which are based on fuzzy control, dynamic subspace divided BP neural network identification method, and fuzzy and neural identification method, by defining the robustness of color space conversion model and evaluation method. The result shows that the device color characteristic methods which are based on fuzzy and neural identification method can make the feature of BP neural network combine with fuzzy control to greatly improve the robustness of model.更多还原