Identification of dragon trees and fruits in ham Thuan Bac growing areas, Phan Thiet city, Binh Thuan province, Vietnam

Abstract

With the development of Computer Vision, we can effectively and accurately identify trees, fruit or object images. But to build a high-performance image dataset for tree identification problems in Agriculture is a challenge. Realizing that Vietnam is a country with strong agriculture with many tropical fruits grown widely such as Dragon fruit, Mangosteen, Mango, Orange, Lychee, Longan … We chose the Dragon Fruit tree for the data set. of my proposed images, all images will be collected using the close-up method, including tasks such as taking photos of Dragon Fruit trees from many angles and in different conditions (weather, temperature, light, …). In this article, we want to improve the data quality of the collected images so we have applied image processing techniques such as noise filtering (using Gaussian filter), image quality enhancement (image rotation), flip the image, zoom out, zoom in, etc.). From the collected Dragon Fruit tree data set, we will propose to use the Faster R–CNN model for this data set to build a tree and Dragon Fruit identification system.

Keywords

• Tree datasets
• Tree recognition
• And classification
• Image processing
• Image enhancement
• Faster R–CNN