In this paper, we propose a Fast Text Detection (FTD) algorithm to automatically identify the text and line art pixels in scanned monochromatic and color documents for enhancing text in printed documents. To simulate the scanning operation, the input image is converted from the RGB space to a Luminance-Chrominance space and is then divided into individual strips. This is followed by a low pass filtering operation on the input strips for removing high frequency noise and to reduce processing time. An edge detection scheme is then applied to the blurred strips to generate corresponding edge-strips. The edge-strips are then subjected to a morphological operation and an edge-based adaptive thresholding simultaneously and the resulting two output strips are merged together to obtain the final candidate text plane. In the text enhancement operation, the original image is first converted into LCH space and the pixels corresponding to the detected text pixels are enhanced via a clipping operation in the L and C channel. This algorithm is highly efficient in terms of memory usage and processing speed and is thus suited to run effectively in low-cost embedded devices.

In this paper, we consider a dual-mode process for the electrophotographic laser printer--a low-frequency halftoning for smooth regions and a high-frequency halftoning for detail regions. These regions are described by an object map that is extracted from the page description language version of the document. This manner of switching screens depending on the local content provides a stable halftone without artifacts in smooth areas and preserves the detail rendering in detail or texture areas. However, when switching between halftones with two different frequencies, jaggies may occur along the boundaries between areas halftoned with low- and high-frequency screens. To reduce the jaggies, our screens obey a harmonic relationship. In addition, we implement a blending process based on a transition region. We propose a nonlinear blending process in which at each pixel, we choose the maximum of the two weighted halftones, where the weights vary according to the position in the transition region. Moreover, we describe an online tone-mapping for the boundary blending process, based on an offline calibration procedure that effectively assures the desired tone values within the transition region.