Open AccessAn Efficient Method for a Specific Case of Detecting Impulse Noise on Scanned Documents
Author(s) -
Petar Prvulović,
Jelena Vasiljević,
Dhinaharan Nagamalai
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5121/csit.2021.111514
Subject(s) - computer science , preprocessor , impulse noise , noise (video) , margin (machine learning) , artificial intelligence , pattern recognition (psychology) , pixel , noise measurement , computer vision , contrast (vision) , impulse (physics) , data mining , noise reduction , image (mathematics) , machine learning , physics , quantum mechanics
This paper explains a method used to detect the presence of impulse noise in a set of scanned documents as a part of OCR preprocessing. As the document set is supposed to be processed in large scale, the primary concern of the noise detection method was efficiency within existing project constraints. Following the nature of noise, the method seeks to detect the presence of noise in document margins. The method works in two stages. First stage is margin detection, based on color spectre analysis. Second stage is noise recognition in margin samples, based on a pixel contrast score. The resulting implementation proved efficient both in terms of detection accuracy and algorithmic complexity.