Hand initialization and tracking using a modified KLT tracker for a computer vision-based breast self-examination system

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2014 - 7th HNICEM 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics, co-located with 10th ERDT Conference

Publication Date

1-1-2014

Abstract

This paper presents a new algorithm for tracking the hand during palpation in a breast self-examination video capture using a modified KLT feature tracker. This is implemented primarily using Shi-Tomasi corner detection and Lucas-Kanade optical flow. A novel hand initialization technique was developed using Shi-Tomasi corner detection, outlier elimination, ellipse fitting, and target estimation in order to locate specifically the finger pads. Then, continuous hand tracking is achieved using Lucas- Kanade optical flow and a novel evaluation and screening of displacement vectors. A dataset of 14 video sequences was used to test the performance of the proposed algorithm. Experiments revealed efficient tracking capability of the algorithm with an overall F-score of 94.61% © 2014 IEEE.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2014.7016244

Disciplines

Biomedical | Electrical and Computer Engineering

Keywords

Breast—Examination--Automation; Self-examination, Medical--Automation; Computer vision in medicine

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