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
