Texture analysis of lace images using histogram and local binary patterns under rotation variation
| Autor: | Adeel Ahmad, Alice Porebski, Denis Hamad, Nicolas Vandenbroucke, Wael Ben Soltana |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique Signal et Image de la Côte d'Opale (LISIC), Université du Littoral Côte d'Opale (ULCO), LAGIS-SI, Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS), Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
feature level fusion
Computer science Local binary patterns Feature extraction Image processing 02 engineering and technology Local Binary Patterns k-nearest neighbors algorithm Histogram 0202 electrical engineering electronic engineering information engineering [INFO]Computer Science [cs] Computer vision texture analysis kNN classifier ComputingMilieux_MISCELLANEOUS business.industry Fourier Transform Histogram matching 020207 software engineering Pattern recognition Lace textile Feature (computer vision) [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] 020201 artificial intelligence & image processing Artificial intelligence score level fusion business Image histogram |
| Zdroj: | 2014 First International Image Processing, Applications and Systems Conference (IPAS) 2014 First International Image Processing, Applications and Systems Conference (IPAS), Nov 2014, Sfax, France. pp.1-5, ⟨10.1109/IPAS.2014.7043325⟩ International Image Processing, Applications and Systems Conference 1st International Image Processing, Applications and Systems conference (IEEE-IPAS'14) 1st International Image Processing, Applications and Systems conference (IEEE-IPAS'14), Nov 2014, Sfax, Tunisia. ⟨10.1109/IPAS.2014.7043325⟩ |
| DOI: | 10.1109/IPAS.2014.7043325⟩ |
| Popis: | International audience; The images of lace textile are particularly difficult to be analyzed in digital form using classical image processing techniques. The major reasons of this difficulty emerge from the complex nature of lace which generally has different textures in its constituents like the background and patterns. In this paper, we study the behavior of Image Histogram (HistI) and Local Binary Patterns (LBP) on image extracts of lace in presence and absence of rotation. We further evaluate two variants of LBP; primarily the LBP Histogram (LBPB) and secondly the Fourier Transform applied on the LBP Histogram (LBPFFT). Consequently, we analyze the contribution of data fusion on feature level and score level in the different experimentations. The classification rate evaluates the discrimination degree of each descriptor via the k nearest neighbors kNN classifier. Experimental results indicate that the LBPB, LBPFFT and HistI combined at score level generate the better performance in absence of transformations. Whereas, LBPFFT and HistI combined at the same level generate the better classification rate, in the presence of rotation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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