Using Mobile Image Recognition System for Nonwood Species Identification in the Field

Abstract

Non-wood forest products (NWFPs) provide important source of income for millions of households worldwide especially for those in rural areas. Especially nonwood plants are main source of income for rural people in many parts of the world. These plants are also consumed by local people for health, nutrition and many other needs. In order to ensure benefits of NWFPs, it is important to identify nonwood plants and determine their population distribution. However, plant identification by using manual method is a complex task to fulfill especially in varying conditions in the field. The leaves are often used to identify plant species based on their visible characteristics. Image recognition systems have been developed to identify plant species by using leaf image. Comparing manual plant identification systems, image recognition systems are easier and, in most cases, more accurate alternatives. In recent years, some mobile applications have been developed to assist people to identify plants by taking pictures of their leaves using smart phones. In this study, it was aimed to investigate the capabilities of the most common mobile image recognition systems in identification of plant species based on leaf images.