Arabic Bank Check Processing: State of the Art

In this paper, we present a general model for Arabic bank check processing indicating the major phases of a check processing system. We then survey the available databases for Arabic bank check processing research. The state of the art in the different phases of Arabic bank check processing is surveyed （i.e., pre-processing, check analysis and segmentation, features extraction, and legal and courtesy amounts recognition）. The open issues for future research are stated and areas that need improvements are presented. To the best of our knowledge, it is the first survey of Arabic bank check processing.

Robust Non-Frontal Face Alignment with Edge Based Texture

This paper proposes a new algorithm, called Edge-based Texture Driven Shape Model （E-TDSM）, for nonfrontal face alignment task. First, the texture is defined as the un-warped edge image contained in the shape rectangle; then, a Bayesian network is constructed to describe the relationship between the shape and texture models; finally, ExpectationMaximization （EM） approach is utilized to infer the optimal texture and position parameters from the observed shape and texture information. Compared with the traditional shape localization algorithms, E-TDSM has the following advantages： 1） the un-warped edge-based texture can better predict the shape and is more robust to the illumination and expression variation than the conventional warped gray-level based texture; 2） the presented Bayesian network indicates the logic structure of the face alignment task; and 3） the mutually enhanced shape and texture observations are integrated to infer the optimal parameters of the proposed Bayesian network using face alignment task demonstrate the effectiveness and robustness EM approach. The extensive experiments on non-frontal of the proposed E-TDSM algorithm.