Classification of Live Moths Combining Texture, Color and Shape Primitives

Abstract

Each year, insect-borne diseases kill more than one million people, and harmful insects destroy tens of billions of dollars worth of crops and livestock. At the same time, beneficial insects pollinate three-quarters of all food consumed by humans. Given the extraordinary impact of insects on human life, it is somewhat surprising that machine learning has made very little impact on understanding (and hence, controlling) insects. In this work we discuss why this is the case, and argue that a confluence of facts make the time ripe for machine learning research to reach out to the entomological community and help them solve some important problems. As a concrete example, we show how we can solve an important classification problem in commercial entomology by leveraging off recent progress in shape, color and texture measures.