Model Development of Marble Quality Identification Using Thresholding, Sobel Edge Detection and Gabor Filter in a Mobile Platform
| Autor: | Marvin Rick G. Forcado, Jheanel E. Estrada |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Local binary patterns Computer science business.industry 020208 electrical & electronic engineering Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Decision tree Pattern recognition Sobel operator 02 engineering and technology Thresholding Random forest Support vector machine 020901 industrial engineering & automation Gabor filter 0202 electrical engineering electronic engineering information engineering Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM). |
| DOI: | 10.1109/hnicem.2018.8666359 |
| Popis: | Organizations in the marble industry use machines to identify the marble slab’s quality which is costly for developing countries like the Philippines. Marble is classified by expert human visually and classification is prone to error. This paper presents a study on marble classification using image processing based on color and texture. Features extraction using Thresholding, Gabor Filtering, Sobel Edge and Local Binary Pattern (LBP). Three supervised learning was used which includes Support Vector Machine, Decision Tree, and Random Forest. 120 marble images were trained and 75 images were used for testing. LBP is consistent with 86.67% accuracy, 0.800 of Kappa and execution-time of 2 seconds using the Decision tree. The Model was applied to the prototype with 82% accuracy to 100 unlabeled images tested with the expert. In conclusion, the developed model can classify the marble quality which is higher than the accuracy from the previous research work applied to the industrial machines. |
| Databáze: | OpenAIRE |
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