Fruits and Vegetables Detection using YOLO Algorithm

S. Kanakaprabha, Dr. Gaddam Venu Gopal, D. Kaleeswaran, D. Hemamalini, Dr. G. Ganeshkumar

Dark Flow, Fruit, OpenCV, Vegetable, YOLO

The robotic harvesting platform's fruit and vegetable detection system is crucial. Due to uneven environmental factors such branch and leaf shifting sunshine, fruit and vegetable clusters, shadow, and so on, the fruit recognition has become more difficult in nowadays. The current method in this work is used to detect different types of fruits and vegetables in different size and shape. This method makes the use of OpenCV, Dark Flow, a TensorFlow variant of the YOLO technique. To train the necessary of network, a range of fruits and vegetable pictures were input into the network. The photos were pre-processed using OpenCV to create manual bounding boxes around the fruits and vegetables before into the training. YOLO detection algorithm is used. In, this method more accurately and rapidly recognizes of an item in an image. After the network has been trained, the test input is sent into the bounding boxes surrounding the recognized fruits and vegetables will be displayed as a consequence.

Received: 08 Jun 2023, Receive in revised form: 10 Jul 2023, Accepted: 18 Jul 2023, Available online: 31 Jul 2023

10.22161/ijaers.107.8