Image Processing in Floriculture Using a robotic Mobile Platform

TL;DR

This paper presents a robotic platform equipped with an image processing system for monitoring and diagnosing floriculture products, enhancing automation and quality control in flower industry practices.

Contribution

It develops a novel robotic monitoring system using image processing algorithms implemented in Matlab for automated flower analysis and diagnostics.

Findings

Successful implementation of image segmentation and feature extraction.

Robotic system can identify, locate, and diagnose flowers automatically.

Enhanced processing speed through image preprocessing and dimension adjustment.

Abstract

Colombia has a privileged geographical location which makes it a cornerstone and equidistant point to all regional markets. The country has a great ecological diversity and it is one of the largest suppliers of flowers for US. Colombian flower companies have made innovations in the marketing process, using methods to reach all conditions for final consumers. This article develops a monitoring system for floriculture industries. The system was implemented in a robotic platform. This device has the ability to be programmed in different programming languages. The robot takes the necessary environment information from its camera. The algorithm of the monitoring system was developed with the image processing toolbox on Matlab. The implemented algorithm acquires images through its camera, it performs a preprocessing of the image, noise filter, enhancing of the color and adjusting the dimension in order to increase processing speed. Then, the image is segmented by color and with the binarized version of the image using morphological operations (erosion and dilation), extract relevant features such as centroid, perimeter and area. The data obtained from the image processing helps the robot with the automatic identification of objectives, orientation and move towards them. Also, the results generate a diagnostic quality of each object scanned.