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ALPHABETS IMAGE IDENTIFICATION USING ADVANCED LOCAL BINARY PATTERN AND CHAIN CODE ALGORITHM
Author(s) -
Daniel Setiawan Cahyono,
Shinta Estri Wahyuningrum
Publication year - 2021
Publication title -
proxies: jurnal informatika
Language(s) - English
Resource type - Journals
ISSN - 2301-9220
DOI - 10.24167/proxies.v2i2.3209
Subject(s) - chain code , binary image , grayscale , preprocessor , computer science , image (mathematics) , artificial intelligence , code (set theory) , pattern recognition (psychology) , edge detection , optical character recognition , digital image , enhanced data rates for gsm evolution , binary number , transformation (genetics) , feature detection (computer vision) , computer vision , algorithm , digital image processing , identification (biology) , image processing , mathematics , arithmetic , biochemistry , chemistry , set (abstract data type) , gene , programming language , botany , biology
Optical Character Recognition (OCR) is a method for computer to process an image that contains some text and then try to find any characters in that image, then convert it to digital text. In this research, Advanced Local Binary Pattern and Chain Code algorithm will be tested to identify alphabets in the image. Several method image preprocessing are also needed, such as image transformation, image rescaling, grayscale conversion, edge detection and edge thinning.

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