This project develops a systematized approach to strawberry feature detection. Evaluating the appearance of a strawberry is necessary to assess the quality of fruit and determine characteristics of different varieties for commercial and breeding purposes. The current method uses visual observations, a highly subjective approach that also relies on experiential knowledge. A systematized, analytical approach to strawberry feature detection would reduce both time and labor. In this project, several key features of a strawberry, such as color, shape, and size, are extracted using machine vision technology and image processing tools in MATLAB. These results can be used to create an algorithmic predictor of strawberry variety characteristics for strawberry producers and breeders.
Eleni Pateras
Cal Poly Undergraduate Program
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