In this work, an approach for feature extraction by support vector machines over images of plants from an aquaponic system is presented. Image processing using Python programming on a low-cost computer connected to a compatible camera is proposed as an aid for preserving modern agricultural systems, under a color, texture and shape feature extraction analysis. The intensity information from images of tomatoes growing in an aquaponic system is exploited in order to obtain an early detection of diseases and nutrient deficiency, as well as a prediction of freshness and time to harvest. Working towards the use of a portable tool for non-destructive measurement on the field; image segmentation, clustering for extraction, classification and comparison of features, are implemented using open source software routines that allow an easier discrimination between plants for a reasonable execution time.
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