Autonomous Ripeness Detection Using Image Processing for an Agricultural Robotic System

This work concerns computer vision and image processing methods for the detection of the ripe and changing tomato fruits. When the lighting or weather is not appropriate for obtaining good quality images, field workers can run extra pre-processing techniques. This work uses Raspberry Pi and Pi Camera hardware; the software is Raspbian running Python 3. OpenCV and HSV color space helps one detect the ripeness. Counting the tomatoes will enable the field workers to prepare labor or equipment by knowing how many tomatoes are ready for harvest and how many will be accessible for that purpose. The Turtlebot will interface this hardware set-up with the robot to navigate the field in order to reach ripe detection.

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