In this paper, we propose a framework for extracting information of interest from forms that contain both machineprinted and handwritten text. The main challenge of data extraction from such documents is in accurately localizing the text regions of interest, and then recognizing the content in these regions. In this paper, we present a novel template matching method that uses Affine Scale-invariant Feature Transformation (ASIFT) to extract key points in a test image and pre-specified templates. Our experimental results show that the proposed method can effectively and accurately locate and extract the data entries for mixed-type forms
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