Devi, Putri Aisyiyah Rakhma and Budiarti, Rizqi Putri Nourma (2020) Image Classification with Shell Texture Feature Extraction Using Local Binary Pattern (LBP) Method. Applied Technology and Computing Science Journal, 3 (1). pp. 48-57. ISSN 2621-4458
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Abstract
Classification procedure that is usually done manually by way of separation based on the texture of the shell shell. Classification is done by looking at objects based on inherent characteristics usually referred to as features / characteristics. Classification by hand can cause accuracy problems. In the image of the shells, texture characteristics are needed to distinguish one type of shell from another. The purpose of this study is to develop a texture feature extraction system for the classification of shell images. The input image is carried out preprocessing and segmenting to separate objects from the background and the image of the separated object is transformed into a grayscale image for the feature extraction process using the Local Binary Pattern method. Based on trials that have been done, the accuracy is quite good, the highest accuracy value occurs in shellfish blood cockles with RBF kernels. While the lowest accuracy is on testing the feather shell image where the accuracy value is 86.6% this result can show that the LBP method with SVM classification is quite reliable in calculating the accuracy for the classification process of shellfish types.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | texture feature extraction, LBP, classification, shell image |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Technique > Program Study of Information Systems |
| Depositing User: | Mr. . Aji |
| Date Deposited: | 10 Jan 2023 01:35 |
| Last Modified: | 10 Jan 2023 01:35 |
| URI: | http://repository.unusa.ac.id/id/eprint/9141 |
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