Agricultural produce Sorting and Grading using Support Vector Machines and Fuzzy Logic
Autor: | Zainul Abidin Md Sharrif, Wong Bing Yit, Nur Badariah Ahmad Mustafa, Aidil Azwin Zainul Abidin, Syed Khaleel Ahmed, Zaipatimah Ali |
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Rok vydání: | 2009 |
Předmět: |
business.product_category
Contextual image classification business.industry Computer science Feature extraction Machine learning computer.software_genre Fuzzy logic Support vector machine Information and Communications Technology Artificial intelligence business MATLAB Grading (education) computer Digital camera computer.programming_language |
Zdroj: | 2009 IEEE International Conference on Signal and Image Processing Applications. |
DOI: | 10.1109/icsipa.2009.5478684 |
Popis: | Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising. |
Databáze: | OpenAIRE |
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