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https://dspace.upt.ro/xmlui/handle/123456789/7085
Titlu: | Novel feature extraction methods for effective texture image and data classifications [articol] |
Autori: | Krishnan, S.Navaneetha Vadivel, P. Sundara Yuvaraj, D. Mathusudhanan, S.R. |
Subiecte: | DTCWT method SVM classifier CCM GLCM KNN classifier |
Data publicării: | 2019 |
Editura: | Timișoara : Editura Politehnica |
Citare: | Krishnan, S.Navaneetha; Vadivel,P. Sundara; Yuvaraj,D.; Mathusudhanan,S.R.: Novel feature extraction methods for effective texture image and data classifications. Timişoara: Editura Politehnica, 2019. |
Serie/Nr. raport: | Journal of Electrical Engineering;Vol 19 No 2 |
Abstract: | Feature Extraction is a process of capturing visual content of images for indexing & retrieval. Texture is a primary property of natural images which is of much importance in the fields of computer vision and computer graphics. Texture study is a type of image analysis producing measurements of the texture. These measurements may be of low- level, such as statistics of local facade or a result of higher level processing, such as segmentation of an image into different regions or the class of the texture present in an image. Identifying the superficial qualities of texture in an image is an important. The proposed work provides novel feature extraction schemes for identifying texture categories. Three frameworks have been proposed for 2D gray level images for classifying the textures.First two frameworks are designed for classifying the textures of gray scale images. The third frame work is proposed for classifying colour images. |
URI: | https://dspace.upt.ro/xmlui/handle/123456789/7085 |
ISSN: | 1582-4594 |
Colecţia: | Articole științifice/Scientific articles |
Fişierele documentului:
Fişier | Descriere | Mărime | Format | |
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BUPT_ART_Krishnan_f.pdf | 948.36 kB | Adobe PDF | Vizualizare/Deschidere |
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