Printing books-on-demand is a new technology that is revolutionizing the book printing and publishing industry. One of the biggest bottlenecks in this process is the conversion of existing books into digital form. This typically involves digitization of original books through scanning, which is a slow and labor-intensive process. Careful attention must be paid to maintain the quality of the reproduced books and in particular of the images they contain. Halftoned image areas in the original books cause the most reproduction problems, as there is the potential that moiré patterns may form when these image areas are re-screened. In order to avoid these moiré patterns, it is necessary to detect the image areas of the document and remove the screen pattern present in those areas. In the past, we have presented techniques to perform these operations in the case of grayscale images. In this article, we extend these techniques to handle color images. We present efficient and robust techniques to segment a color document into halftone image areas, detect the presence and frequency of screen patterns in halftone areas and suppress the detected screens. Halftoned image areas are segmented by using a measure of image activity; image activity is low in text areas and high in halftoned areas. We use 2-D Fourier spectral analysis to identify the screen frequencies present. The screens are then suppressed by low-pass filtering. Our technique speeds up the conversion process of books to digital form, and overcomes quality problems in the reproduction of halftoned images.