Mangrove Leaves

This dataset consists of images of seven types of mangrove leaves acquired using a smartphone camera. The image acquisition process was carried out by considering variations in angle, distance, and direction to ensure diverse visual perspectives. Each image captures the visual characteristics of the leaf surface, such as color, texture, and vein patterns, which can serve as important features in the classification and identification of mangrove species using image processing and machine learning methods. This data collection approach aims to produce a diverse, representative, and realistic dataset that can serve as a foundation for developing a reliable mangrove leaf detection model under various lighting and environmental conditions. The dataset consists of seven species of mangrove leaves, namely: Avicennia marina (Am), Avicennia officinalis (Ao), Bruguiera gymnorhiza (Bg), Heritiera littoralis (Hl), Lumnitzera littorea (Lt), Rhizophora apiculata (Ra), and Sonneratia caseolaris (Sa). Each species contains 1,000 images, resulting in a comprehensive and balanced dataset for further analysis and model training.