Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals – VISION AND IMAGE PROCESSING (VIP) RESEARCH GROUP

Dorothy Lui

Dorothy Lui — Thu, 23 Mar 2023 19:29:04 +0000

I completed my bachelor’s in Mechatronics Engineering at the University of Waterloo in 2012. I am now pursuing my master’s in Systems Design Engineering under the supervision of Prof. Wong. I was first exposed to image processing while working on in vivo bone implant images to determine bone porosity at the UW Rapid Prototyping Lab. Then, I worked at Colibri Technologies applying digital signal processing to ultrasound images.

Supervisors

Alexander Wong

Research interests

I am passionate about image processing and pattern recognition, particularly in applications in biomedical imaging. My current research involves developing new algorithms to automate segmentation of particular features in biomedical images.

Research topics

Biomedical Imaging
Computer Vision
Image Segmentation/Classification
Multiresolution Techniques
Stochastic Models

Research demos

Bias Field Correction in Endorectal Diffusion Imaging
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Enhanced Low-dose Computed Tomography
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

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Christian Scharfenberger

Christian Scharfenberger — Thu, 23 Mar 2023 16:18:05 +0000

I was a post-doctoral fellow in the Vision and Image Processing Lab from 10/2011-12/2014. I collaborated with the professors David Clausi, Alexander Wong, John Zelek, and Steven Waslander in the areas of image processing, computer vision, and robotics. Please find a selection of research projects I am/was involved with listed below.

Email: cscharfenberger@uwaterloo.ca

Supervisors

Alexander Wong, David Clausi

Research interests

My research interests are in the fields of computer vision, image processing, and pattern recognition with an emphasis on saliency computation, camera calibration and stereo vision. I am particularly interested in practical applications of computer vision and image processing methods to problems in robotics and driver assistance systems.

Research topics

Biomedical Imaging
Computer Vision
Image Segmentation/Classification
Video Analysis

Research demos

Coded Hemodynamic Imaging
Computer Vision for Autonomous Robots
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation
Statistical Textural Distinctiveness for Salient Region Detection in Natural Images
Stereo Vision for Dimension Estimation

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

Top

Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals

vipadmin — Tue, 21 Mar 2023 14:47:35 +0000

Active contours are a popular approach for object segmentation that uses an energy minimizing spline to extract an objects boundary. Non-parametric approaches can be computationally complex while parametric approaches can be impacted by parameter sensitivity. A decoupled active contour (DAC) overcomes these problems by decoupling the external and internal energies and optimizing them separately. However a drawback of this approach is its reliance on the edge gradient as the external energy. This can lead to poor convergence toward the object boundary in the presence of weak object and strong background edges. To overcome these issues with convergence, a novel approach is proposed that takes advantage of a sparse texture model which explicitly considers texture for boundary detection. The approach then defines the external energy as a weighted combination of textural and structural variation maps and feeds it into a multi-functional hidden Markov model for more robust object boundary detection. The enhanced decoupled active contour (EDAC) is qualitatively and visually analyzed on two natural image datasets as well as Brodatz images. The results demonstrate that EDAC selectively combines texture and structural information to extract the object boundary without impact on computation time and a reliance on color.

Illustration of the architecture for the EDAC approach: The multi-functional variation map of the source image is derived using a weighted combination of the textural and structural variation maps, where the textural variation map is determined using the sparse texture model. This map is used to formulate the active contour by optimizing the external and internal energies to result in the segmented image.

From left to right: Source image, sparse texture model, external energy, snake and ground truth are shown for two examples where structural and textural variations enable effective active contour segmentation.

Code

If you are interested in our software for segmenting images based on enhanced decoupled contours, we would be happy to share demo code (MATLAB) for research purposes only. [Disclaimer] [Code]

Downloads

Disclaimer.txt
TIP2014_EDAC_DEMO.zip

Related people

Directors

Students

Alumni

Related research areas

Computer Vision

Image Segmentation/Classification

Related publications

Journal Articles

Conference Papers

Alexander Wong

Alexander Wong — Thu, 23 Feb 2023 21:38:59 +0000

Alexander Wong is currently the Canada Research Chair in Medical Imaging Systems and an assistant professor in the Department of Systems Design Engineering at the University of Waterloo. He had previously received his B.A.Sc. degree in Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2005, his M.A.Sc. degree in Electrical and Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2007, and his Ph.D. degree Systems Design Engineering from the University of Waterloo, ON, Canada in 2010. He was also a NSERC postdoctoral research fellow at Sunnybrook Health Sciences Centre. He has published over 450 refereed journal and conference papers, as well as patents, in various fields such as computational imaging, artificial intelligence, computer vision, and multimedia systems. He has received numerous awards including three Outstanding Performance Awards, a Distinguished Performance Award, an Engineering Research Excellence Award, a Sandford Fleming Teaching Excellence Award, an Early Researcher Award from the Ministry of Economic Development and Innovation, a Best Paper Award at the NIPS Workshop on NIPS Workshop on Transparent and Interpretable Machine Learning (2017), a Best Paper Award at the NIPS Workshop on Efficient Methods for Deep Neural Networks (2016), two Best Paper Awards by the Canadian Image Processing and Pattern Recognition Society (CIPPRS) (2009 and 2014), a Distinguished Paper Award by the Society of Information Display (2015), two Best Paper Awards for the Conference of Computer Vision and Imaging Systems (CVIS) (2015,2017), Synaptive Best Medical Imaging Paper Award (2016), two Magna Cum Laude Awards and one Cum Laude Award from the Annual Meeting of the Imaging Network of Ontario, CIX TOP 20 (2017), AquaHacking Challenge First Prize (2017), Best Student Paper at Ottawa Hockey Analytics Conference (2017), and the Alumni Gold Medal.

Students

Supervision – Current

PDF

ph.D.

M.A.Sc.

Supervision – Completed

PDF

ph.D.

M.A.Sc.

Research topics

Biomedical Imaging
Computer Vision
Discovery Radiomics
Evolutionary Deep Intelligence
Image Segmentation/Classification
Multiresolution Techniques
Remote Sensing
Scientific Imaging
Stochastic Models
Video Analysis

Research demos

Action Recognition in Video
Bias Field Correction in Endorectal Diffusion Imaging
Coded Hemodynamic Imaging
Correlated Diffusion Imaging
Disparate Scene Registration
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Enhanced Low-dose Computed Tomography
Grid Seams: A fast superpixel algorithm for real-time applications
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation
Image Denoising
Multiplexed Optical High-coherence Interferometry
SAR Sea Ice Image Synthesis
Skin Cancer Detection
Statistical Textural Distinctiveness for Salient Region Detection in Natural Images
Stereo Vision for Dimension Estimation

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

Top

David Clausi

David A Clausi — Mon, 13 Feb 2023 20:18:05 +0000

I completed my Ph.D. in Systems Design Engineering in 1996 and immediately afterwards, I worked in software medical imaging field at Agfa (nee Mitra) in Waterloo, Ontario. I started my academic career in 1997 as an Assistant Professor in Geomatics Engineering at the University of Calgary, Canada. In 1999, I returned to my alma mater and I am now a Professor specializing in the fields of Intelligent and Environmental Systems. In addition, I was the Associate Chair – Graduate Studies (2009-2012). I was the Co-chair of IAPR Technical Committee 7 – Remote Sensing during 2004-2006. I have numerous recognitions, including received five Outstanding Performance Awards, three Distinguished Performance Awards, the Sanford Fleming Teaching Excellence Award, and a University of Calgary Teaching Excellence Award. In 2010, I received the award for “Research Excellence and Service to the Research Community” by the Canadian Image Processing and Pattern Recognition Society (CIPPRS). In 2012, I received the Engineering Research Excellence Award.

Currently, I am the Associate Dean – Research & External Partnerships within the Faculty of Engineering, responsible for all research related activities in the largest Engineering school in Canada.

Research interests

My research interests are in the fields of computer vision, image processing, and pattern recognition with an emphasis on the automated interpretation of SAR (synthetic aperture radar) and sports analytics (ice hockey). I am an active interdisciplinary and multidisciplinary researcher, publishing refereed journal and conference papers in the diverse fields of remote sensing, sports analytics, computer vision, algorithm design, and biomechanics. My research efforts have led to successful commercial implementations including creating and selling a startup company (CREZ).