Scanned document enhancement based on fast text detection
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.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)