DESAIN MODEL PENGENALAN TANAMAN MENGGUNAKAN CITRA DAUN 3D (MODEL DESIGN OF PLANT RECOGNITION USING 3D LEAF IMAGES )

Abstract

Understanding of the view (scene) and 3D object recognition is one of the magnificent challenges in computer vision. A wide variety of techniques and goals, such as structure from motion, optical flow, stereo, edge detection, and segmentation, can be viewed as subtasks in scene understanding and object recognition. Many methods can be applied by previous investigators. On the contrary, this research is focused on highlevel representation for scenery and objects, especially physical representation recognize 3D view of the underlying image. This study aims to answer the following questions: • How to relate 2D image with a 3D scene, and how we can take advantage of the relationship perspective? • How does the physical scene space can be modeled, and how to estimate the space scene of an image? • How to represent and recognize objects in a way that is robust to changes in viewpoint? • How can use the knowledge and perspective of the scene to improve the recognition space, or vice versa? In this study, carried out the stages of development of the plant recognition system based on 3D stereo images leaves, namely: image enhancement and segmentation, stereo correspondence, disparity map calculation and depth maps, feature extraction using Gray Level Coocurence Matrix, and classification using Euclidian distance. The results obtained in this study indicate that the recognition accuracy of the plant with the highest 3D image of the leaf is 83.3% to recognize 3 varieties of plants. While to recognize 9 varieties of plants obtained low accuracy. The low accuracy is due to the quality of the disparity and depth maps are possible for further research.

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