Identification of river hydromorphological features using histograms of oriented gradients cascaded to the Viola-Jones algorithm
College
Gokongwei College of Engineering
Department/Unit
Mechanical Engineering
Document Type
Article
Source Title
International Journal of Mechanical Engineering and Robotics Research
Volume
8
Issue
2
First Page
289
Last Page
292
Publication Date
1-1-2019
Abstract
In this paper, a quadcopter equipped with a camera was used to capture images from a river. These captured images were used as training data in the automated detection program used to identify the hydromorphological features in the area of the river such as trees, roofs, roads and the shore. The histogram of oriented gradient with support vector machine classifier was cascaded with the Viola Jones Algorithm in order to recognize hydromorphological features. Testing was done using different images to verify the effectiveness of the detection system compared with previous studies. System evaluation and success of the cascaded system was determined using the percentage of correct detected features in the image. The results showed that the cascaded system has increased the accuracy compared to the implementation with only the Viola Jones Algorithm. © 2019 Int. J. Mech. Eng. Rob. Res.
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Digitial Object Identifier (DOI)
10.18178/ijmerr.8.2.289-292
Recommended Citation
Cuevas, J., Chua, A., Sybingco, E., & Bakar, E. (2019). Identification of river hydromorphological features using histograms of oriented gradients cascaded to the Viola-Jones algorithm. International Journal of Mechanical Engineering and Robotics Research, 8 (2), 289-292. https://doi.org/10.18178/ijmerr.8.2.289-292
Disciplines
Mechanical Engineering
Keywords
Drone aircraft in remote sensing; Support vector machines; Rivers
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