Building accurate knowledge of the identity and the geographic distribution of plants is essential for future biodiversity conservation. The current rate of extinction is largely the result of direct and indirect human activities. The systematic and concise overview will also be helpful for beginners in those research fields, as they can use the comparable analyses of applied methods as a guide in this complex activity.īiodiversity is declining steadily throughout the world. Our results are relevant to researches in ecology as well as computer vision for their ongoing research.
Furthermore, we compare methods based on classification accuracy achieved on publicly available datasets. After a careful analysis of these studies, we describe the applied methods categorized according to the studied plant organ, and the studied features, i.e., shape, texture, color, margin, and vein structure. We identified 120 peer-reviewed studies, selected through a multi-stage process, published in the last 10 years (2005–2015). This paper is the first systematic literature review with the aim of a thorough analysis and comparison of primary studies on computer vision approaches for plant species identification. The availability and ubiquity of relevant technologies, such as, digital cameras and mobile devices, the remote access to databases, new techniques in image processing and pattern recognition let the idea of automated species identification become reality.
Today, there is an increasing interest in automating the process of species identification. This creates a hard to overcome hurdle for novices interested in acquiring species knowledge. The identification of plants by conventional keys is complex, time consuming, and due to the use of specific botanical terms frustrating for non-experts. Species knowledge is essential for protecting biodiversity.