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.