Automatic Optical Imaging System for Mango Fruit using Hyperspectral Camera and Deep Learning Algorithm

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Pushpendra Kumar Verma
Paresh Pathak
Bhupendra Kumar


This research paper explores focused on developing an automatic mango fruit quality detection system using a combination of artificial intelligence and the Internet of Things technologies. The system utilizes a hyperspectral camera to capture images of the mango fruit and image processing techniques to analyze the images. Deep learning algorithms are employed to classify the mango fruit based on quality parameters such as ripeness, size, and color. The proposed system aims to automate the mango fruit quality inspection process, improve the accuracy of quality assessment, and reduce human error. The results of this research could have applications in the food industry, specifically in the field of fruit quality inspection and sorting. Mango Fruit, Hyperspectral Camera, Image Processing, Deep Learning algorithms, Quality Recognition.

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How to Cite
Verma, P. K. ., Pathak, P. ., Kumar, B. ., Himani, H., & Preety, P. (2023). Automatic Optical Imaging System for Mango Fruit using Hyperspectral Camera and Deep Learning Algorithm. International Journal on Recent and Innovation Trends in Computing and Communication, 11(5s), 112–117.


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