Towards Integrated Image Contrast Models in Segmentation of Trees

Abstract

Computer vision is an area in high demand which is bringing new trends for urban and rural applications. Some examples can be found in autonomous navigation projects, monitoring services, fruits/grain harvesting, pest control, and so forth. However, drastic or even unperceptive changes in the image acquisition process limit the development of these applications, especially for problems that require solutions for uncontrolled environments such as outdoor areas. Thus, the definition of what a machine is looking at is a challenging task. In this study, we dealt with the image segmentation problem in order to develop a method to delineate tree trunks, their branches, and foliage. As tree detection is a crucial topic in mobile robotics, we investigated it to give an initial interpretation of external scenes. We prepared an image dataset to validate the proposal in which two classes were defined, tree and non-tree. The pixels of each image were classified based on the proposed method, and the results show that our method obtained a positive result of 91% accuracy.

Publication
In Proceedings of 32nd IEEE Canadian Conference of Electrical and Computer Engineering (CCECE 2019)
Gabriel Vieira
Gabriel Vieira
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.

Thamer Nascimento
Thamer Nascimento
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

Related