Advances in Automatic Insect Classification

Abstract

Entomology has been deeply rooted in various cultures since prehistoric times for the purpose of agriculture. Nowadays, many scientists are interested in the field of biodiversity in order to maintain the diversity of species within our ecosystem. Out of 1.3 million known species on this earth, insects account for more than two thirds of these known species. Since 400 million years ago, there have been various kinds of interactions between humans and insects. There have been several attempts to create a method to perform insect identification accurately. Great knowledge and experience on entomology are required for accurate insect identification. Automation of insect identification is required because there is a shortage of skilled entomologists. This paper provides a review of the past literature in vision-based insect recognition and classifications. Over the past decades, automatic insect recognition and classification has been given extra attention especially in term of crop pest and disease control. This paper details advances in insect recognition, discussing representative works from different types of method and classifiers algorithm. Among the method used in the previous research includes color histogram, edge detection and feature extraction (SIFT vector). We provides discussion on the state-of-the-art and provides perspective on future research direction in insect recognition and classification problem.