LOCAL BINARIZATION FOR DOCUMENT IMAGES CAPTURED BY CAMERAS WITH DECISION TREE

Abstract: Character recognition in a document image captured by a digital camera requires a good binary image as the input for the separation the text from the background. Global binarization method does not provide such good separation because of the problem of uneven levels of lighting in images captured by cameras. Local binarization method overcomes the problem but requires a method to partition the large image into local windows properly. In this paper, we propose a local binariation method with dynamic image partitioning using integral image and decision tree for the binarization decision. The integral image is used to estimate the number of line in the document image. The number of line in the document image is used to devide the document into local windows. The decision tree makes a decision for threshold in every local window. The result shows that the proposed method can separate the text from the background better than using global thresholding with the best OCR result of the binarized image is 99.4%.

Keywords: binarization; binerisasi; citra dokumen; decision tree; document images; image partitioning; local window; membagi image; window lokal

Author: Naser Jawas, Randy Cahya Wihandika, Agus Zainal Arifin

Journal Code: jptkomputergg120008

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