Classification of leaf epidermis microphotographs using texture features

We present the results of a Gray Level Co-occurrence Matrix (GLCM) analysis for two sets of leaf epidermis images for the adaxial (20×_H) and abaxial sides (20×_E). The leaves were collected from a dry forest in Mona Island which is located between the Dominican Republic and Puerto Rico. For each set of images (GLCM) texture features were calculated namely the energy, correlation, contrast, absolute value, inverse difference, homogeneity, and entropy. From the calculated statistics a features matrix was obtained for each image and randomly divided into training set and test set using the hold-out method. In this method 70% of the images were considered as a training set and 30% as the test set. For each training and test set a linear discrimination analysis (LDA) was performed resulting in a average correct classification percent of 90% for the abaxial side in comparison with 80% for the adaxial side.