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

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

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 develop...

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Bibliographic Details
Main Authors: Masilang, Rey Anthony A., Cabatuan, Melvin K., Dadios, Elmer P.
Format: text
Published: Animo Repository 2014
Subjects:
Breast—Examination > Automation
Self-examination, Medical > Automation
Computer vision in medicine
Biomedical
Electrical and Computer Engineering
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/4020
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Institution: De La Salle University
Description
Summary: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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