A Color Moments-Based Method for Detection of Honey Bee Diseases

Since the inception of natural life, honey bees have constituted one of the most significant natural elements of pollination. It is therefore imperative to ensure the continued health of bees in order to maintain the bee population. The health of honey bees is threatened by five main diseases. This study proposes a novel, lightweight method for the detection of the five most prevalent diseases affecting honey bees. The method is based on color moments and provides sensitive feature extraction for the detection of color changes in images of bees that have been intensively coloured. The mean, variance and skewness values were calculated for each of the red, green and blue channels from the bee images, resulting in the extraction of nine features. The extracted features were then classified using a support vector machine (SVM). It was observed that the majority of the obtained results exhibited superior performance compared to deep learning solutions.