Various Approaches in Plant Species Identification and Plant Disease Detection Using Digital Images of Leaves

Plants and trees are an inevitable part of our life. All these species contribute to biodiversity, provide clean and fresh air, prevent soil erosion, home remedy, and many more. Acquiring knowledge about species is essential for protecting biodiversity. The identification of plants by conventional methods is complex and time-consuming for novices. Also, many species are endangered because of human encroachment and due to diseases affecting plants. These plant diseases cause economic, social, and ecological losses. In this context, diagnosing diseases accurately and timely and doing the necessary control measures is of the utmost importance. There have been many technological advancements in the area of computer vision to identify plant species and diseases automatically. This paper aims to present various approaches in leaf recognition and disease detection using digital images of leaves. Various phases in image classification using conventional machine learning models and deep learning techniques have been discussed. A comparative study on various paper works and their performance have also been analyzed.