Applicability of computer vision in seed identification: deep learning, random forest, and support vector machine classification algorithms

ABSTRACT The use of computer image analysis can assist the extraction of morphological information from seeds, potentially serving as a resource for solving taxonomic problems that require extensive training by specialists whose primary method of examination is visual identification. We propose to test the ability of deep learning, SVM and random forest algorithms to classify seeds from twelve species of aquatic plants as an alternative to traditional classification methods. A total of 150 seeds of the species were collected. The attributes of colour, shape, and texture were analysed through t...