To over come the drawbacks existing in current measurement methods for detecting and controlling colors in printing process, a new model for color separation and dot recognition is proposed from a view of digital imag...To over come the drawbacks existing in current measurement methods for detecting and controlling colors in printing process, a new model for color separation and dot recognition is proposed from a view of digital image processing and patter recognition. In this model, firstly data samples are collected from some color patches by the Fuzzy C-Means (FCM) method; then a classifier based on the Cerebellar Model Articulation Controller (CMAC) is constructed which is used to recognize color pattern of each pixel in a microscopic halftone image. The principle of color separation and the algorithm model are introduced and the experiments show the effectiveness of the CMAC-based classifier as opposed to the BP network.展开更多
文摘To over come the drawbacks existing in current measurement methods for detecting and controlling colors in printing process, a new model for color separation and dot recognition is proposed from a view of digital image processing and patter recognition. In this model, firstly data samples are collected from some color patches by the Fuzzy C-Means (FCM) method; then a classifier based on the Cerebellar Model Articulation Controller (CMAC) is constructed which is used to recognize color pattern of each pixel in a microscopic halftone image. The principle of color separation and the algorithm model are introduced and the experiments show the effectiveness of the CMAC-based classifier as opposed to the BP network.
