CHACT: Convex Hull Enabled Active Contour Technique for Salient Object Detection

In the domain of computer vision research, human's capability to distinguish salient objects from background has become an important ingredient. So far, the researchers are not able to propose an approach that balances the tradeoff between the computation time needed by humans and detection acc...

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Bibliographic Details
Published in:IEEE access 2018-01, Vol.6, p.22441-22451
Main Authors: Singh, Maheep, Govil, M. C., Pilli, Emmanuel Shubhakar
Format: Article
Language:English
Subjects:
Accuracy
Active contour
Active contours
Bayes methods
Computational geometry
Computational modeling
Computer vision
Computing time
Contours
Convexity
corner detection
edge detection
Error analysis
Feature extraction
Image edge detection
Object detection
Object recognition
Salience
salient object
Shape
Visualization
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Summary:In the domain of computer vision research, human's capability to distinguish salient objects from background has become an important ingredient. So far, the researchers are not able to propose an approach that balances the tradeoff between the computation time needed by humans and detection accuracy. This paper highlights an improved salient object detection (SOD) accuracy technique which does not demand high computation time. The accuracy of convex hull enabled active contour technique (CHACT) model is assessed with area under the curve, recall, precision, F-measure, mean absolute error, and computation time on six available publicly image datasets. The computation time of CHACT is comparatively less than many existing approaches and also improved accuracy for SOD.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2826924