Abstract
In this paper, we present a method of region analysis for business card images acquired in a PDA (personal digital assistant) using DCT and information pixel (IP) density. The proposed method consists of three parts: region segmentation, information region (IR) classification, and character region (CR) classification. In the region segmentation, an input business card image is partitioned into 8 × 8 blocks and the blocks are classified into information blocks (IBs) and background blocks (BBs) by a normalized DCT energy. The input image is then segmented into IRs and background regions (BRs) by region labeling on the classified blocks. In the IR classification, each IR is classified into CR or picture region (PR) by using a ratio of DCT energy of edges in horizontal and vertical directions to DCT energy of low frequency components and a density of IPs. In the CR classification, each CR is classified into large CR (LCR) or small CR (SCR) by using the density of IPs and an averaged run-length of IPs. Experimental results show that the proposed region analysis yields good performance for test images of several types of business cards acquired in a PDA under various surrounding conditions. In addition, error rates of the proposed method are shown to be 2.2–10.1% lower in region segmentation and 7.7% lower in IR classification than those of the conventional methods.
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Jang, I.H., Kim, C.H., Kim, N.C. (2005). Region Analysis of Business Card Images Acquired in PDA Using DCT and Information Pixel Density. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_31
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DOI: https://doi.org/10.1007/11558484_31
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