THE IMAGE PROCESSING IN A VISION SYSTEM-BASED SIZE INSPECTION FOR DRIED FLATTENED BANANAS
Keywords:
Dried flattened bananas, Drying bananas, Images processing, Inspection, Vision systemAbstract
The bananas are an economically significant fruit in Thailand, both for domestic consumption and export. Thailand has opportunities to further expand the value of exports. This includes the development of various banana products, especially dried bananas, which is a method of transforming regular bananas into higher-value products. In the distribution of dried flattened bananas, they are sorted into two groups: small and large sizes. Currently, the size sorting of dried flattened bananas is done manually. The human-based size sorting varies among individuals due to the lack of standardized criteria for distinguishing small and large sizes. Furthermore, this manual process can lead to fatigue, especially when working for extended periods of time. For this reason, the aim of this research is to develop an automated system for automatically sorting the sizes of dried flattened bananas using a vision system with LabVIEW software. The criteria for size sorting are as follows: large-sized bananas must have a length greater than 77 mm, and the surface area captured by the low-cost web camera must be no less than 2780 mm². Based on the experimental results, the sorting was divided into three categories: detecting only small-sized dried bananas, detecting only large-sized ones, each with a quantity of 50 pieces, and detecting a mixture of small and large sizes, with a total quantity of 50 pieces (25 of each size). The accuracy of the program for detecting small-sized dried bananas, large-sized ones, and the mixed sizes was found to be 96.00%, 94.00%, and 94.00%, respectively.
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