Proc. SPIE. 5296, Document Recognition and Retrieval XI
KEYWORDS: Optical filters, Cameras, Image processing, Digital filtering, Personal digital assistants, Image filtering, Image classification, Optical character recognition, Yield improvement, Binary data
In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images of ill conditions acquired by personal digital assistant (PDA) cameras. In the proposed method, a business card image is first partitioned into blocks of 8×8 and the blocks are then classified into character blocks (CBs) and background blocks (BBs) for locally adaptive processing. Each CB is windowed with 24×24 rectangular window
centering around the CB and the windowed blocks are improved by the preprocessing filter MQF, in which the scheme of threshold selection in QF is modified. The 8×8 center block of the improved block is binarized with the threshold. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the quality of binary images obtained by the proposed method is much better than that by the conventional global binarization (GB)
using QF. In addition, the proposed method yields about 43% improvement of character recognition rate over the GB using QF.