Combined cosine-linear regression model similarity with application to handwritten word spotting

The similarity or the distance measure have been used widely to calculate the similarity or dissimilarity between vector sequences, where the document images similarity is known as the domain that dealing with image information and both similarity/distance has been an important role for matching and...

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Bibliographic Details
Published inInternational journal of electrical and computer engineering (Malacca, Malacca) Vol. 10; no. 3; p. 2367
Main Authors Elfakir, Youssef, Khaissidi, Ghizlane, Mrabti, Mostafa, Chenouni, Driss, Boualam, Manal
Format Journal Article
LanguageEnglish
Published Yogyakarta IAES Institute of Advanced Engineering and Science 01.06.2020
Subjects
Decision making
Distance measurement
Handwriting
Matching
Pattern recognition
Regression analysis
Regression models
Similarity
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Summary:The similarity or the distance measure have been used widely to calculate the similarity or dissimilarity between vector sequences, where the document images similarity is known as the domain that dealing with image information and both similarity/distance has been an important role for matching and pattern recognition. There are several types of similarity measure, we cover in this paper the survey of various distance measures used in the images matching and we explain the limitations associated with the existing distances. Then, we introduce the concept of the floating distance which describes the variation of the threshold’s selection for each word in decision making process, based on a combination of Linear Regression and cosine distance. Experiments are carried out on a handwritten Arabic image documents of Gallica library. These experiments show that the proposed floating distance outperforms the traditional distance in word spotting system.
ISSN:2088-8708
2088-8708
DOI:10.11591/ijece.v10i3.pp2367-2374