Combined cosine-linear regression model similarity with application to handwritten word spotting
| Autor: | Manal Boualam, Driss Chenouni, Ghizlane Khaissidi, Mostafa Mrabti, Youssef Elfakir |
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| Rok vydání: | 2020 |
| Předmět: |
Matching (statistics)
General Computer Science Computer science business.industry Pattern recognition Spotting Similarity measure Measure (mathematics) Distance measures Similarity (network science) Pattern recognition (psychology) Artificial intelligence Electrical and Electronic Engineering business Word (computer architecture) |
| Zdroj: | International Journal of Electrical and Computer Engineering (IJECE). 10:2367 |
| ISSN: | 2088-8708 |
| DOI: | 10.11591/ijece.v10i3.pp2367-2374 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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