In recognizing characters written on forms, it often happens that characters overlap with pre-printed form lines. In order
to recognize overlapped characters, removal of the line and restoration of the broken character strokes caused by line
removal are generally conducted. But it is not easy to restore the broken character strokes accurately especially when the
direction of the line and the character stroke are almost same. In this paper, a novel recognition method of line-touching
characters without line removal is proposed in order to avoid the difficulty of the stroke restoration problem. A line-touching
character is recognized as a whole by matching with reference character features which include a line feature.
And the reference features are synthesized dynamically from a character feature and a line feature based on the touching
condition of an input line-touching character string. We compared the performance of the proposed method with a
conventional method in which a touching line is removed leaving the overlapped character stroke by mathematical
morphology. Experimental results show that proposed method can achieves 96.26% character recognition rate whereas
the conventional method achieves 92.77%.
KEYWORDS: Distortion, Digital cameras, Image processing, Optical character recognition, Cameras, 3D modeling, Process modeling, Error analysis, Image analysis, 3D image processing
Distortion correction methods for digital camera document images of thick volumes or curved papers become important
for camera-based document recognition technologies. In this paper we propose a novel distortion correction method for
digital camera document images based on "shape from parallel geodesics." This method considers the following features:
parallel lines corresponding to character strings or ruled lines of tables on extended surface become parallel geodesics on
a curved paper surface and a smoothly curved paper can be modeled by a ruled surface, which is sweep surface of rulings.
The projected geodesics and rulings exist in the input image derived from perspective transformation. The presented
method extracts the projected geodesics, estimates the projected rulings in the input image, estimates the ruled surface
that models the curved paper, and generates the corrected image, in this order. The projected rulings are estimated by the
condition derived from only parallelism of geodesics without the requirements for equal spacing. This method can
estimate the ruled surface model directly by numerical operations of differentiation, integration and matrix inversion
without any iterative calculation. We also report on experiments that show the effectiveness of the proposed method.
For feasible recognition having many categories such as Japanese character recognition, fast matching algorithms are necessary because the matching process occupies most of recognition time. In addition, for improving recognition accuracy, the matching process must use more complicated discrimination functions or a higher dimensional feature space, which involves higher computational costs. Therefore, pre-classification is used, which outputs a set of candidate categories to decrease the number of computations of the complicated discrimination functions.
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