Research Output
A review on contact lens inspection
Defects Detection Algorithm of Harumanis Mango for Quality Assessment Using Colour Features Extraction
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Publication
Over the year, contact lens detection has attracted attention and interest from many researchers to study further in this field of inspection. This paper provides a comprehensive review of the existing literature surrounding contact lens inspection methods. In this paper, contact lens-related, defects-related, and inspection methods related are described in detail. To detect contact lenses in a single image and also multi-image, numerous techniques have been developed and this paper is aimed at classifying and evaluating these algorithms. Also, contact lens inspection based on conventional and artificial intelligence methods will be discussed in detail. The industrial production process of contact lenses probably needs to be constructed with advanced tools based on recent technologies so that they can help in the inspection system to achieve accurate results of the inspection and reduce processing time.
Publication
Visual defects detection is one of the main problems in the post-harvest processing caused a major production and economic losses in agricultural industry. Manual fruits detection become easy when it is done in small amount, but the result is not consistent which will generate issue in fruit grading. A new fruit quality assessment system is necessary in order to increase the accuracy of classification, more consistencies, efficient and cost effective that would enable the industry to grow accordingly. In this paper, a method based on colour feature extraction for the quality assessment of Harumanis mango is proposed and experimentally validated. This method, including image background removal, defects segmentation and recognition and finally quality classification using Support Vector Machine (SVM) was developed. The results show that the experimental hardware system is practical and feasible, and that the proposed algorithm of defects detection is effective.