H
Heng-Da Cheng
Researcher at Utah State University
Publications - 237
Citations - 11404
Heng-Da Cheng is an academic researcher from Utah State University. The author has contributed to research in topics: Image segmentation & Fuzzy logic. The author has an hindex of 49, co-authored 234 publications receiving 10214 citations. Previous affiliations of Heng-Da Cheng include Halifax & Harbin Institute of Technology.
Papers
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Journal Article
Automated real-time pavement crack deflection/classification system
Heng-Da Cheng,Chris Glazier +1 more
TL;DR: This Innovations Deserving Exploratory Analysis (IDEA) project refined and evaluated in the field an automated high resolution imaging system to detect and classify pavement cracks in real time at highway speeds and is ready for surveying pavement distress on highways.
Journal ArticleDOI
Synthesized images for pattern recognition
Mario Miyojim,Heng-Da Cheng +1 more
TL;DR: Generating graphic images by computer with characteristics close enough to reality for testing new pattern recognition algorithms will save time, money and resources at research sites where quality graphics can be rendered.
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Color image segmentation based on neutrosophy
TL;DR: This work introduces neutrosophy to color image segmentation and develops a novel unsupervised algorithm that can handle the segmentation tasks well and can even process noisy images with better accuracy and show its noise-tolerant ability.
Proceedings ArticleDOI
A novel quantitative measurement for thyroid cancer detection based on elastography
TL;DR: A new effective, accurate, and quantitative metric using computer aided diagnosis (CAD) techniques is proposed in this paper and results confirm that the method is more accurate and robust than color score and strain ratio.
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An Effective Non-rigid Registration Approach for Ultrasound Image Based On “Demons” Algorithm
TL;DR: A fully automatic non-rigid image registration algorithm based on demons algorithm is proposed for registration of ultrasound images and demonstrates that the proposed method can register ultrasound images efficiently, robust to noise, quickly and automatically.