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Integrated Colormap and ORB detector method for feature extraction approach in augmented reality

  • 1179: Multimedia Software Engineering: Challenges and Opportunities
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Abstract

Augmented Reality (AR) is a technology that addition of virtual objects into the real-world environment. AR technology uses images recognition approaches to recognize objects. The objects can be easily recognized if rich in details, have good contrast, and have no repetitive patterns. A feature-based technique called Natural Feature Tracking (NFT) system can be used to recognize physical objects in markerless AR. The features such as blob, edge, and corner in the object are extracted by the feature detector and descriptor before recognizing process. The extraction feature is the most important thing in the recognition process because it can determine accurate results. ORB detector is a feature extractor were suitable for real-time tracking in AR because it has speed, efficiency, and a high quantity of features detected and extracted. However, before detecting and describing the features, ORB detector uses the Grayscale Image Generation (GIG) process to change color images into grayscale images. We found some features extracted using the GIG process not extracted perfectly. ORB detector is influenced by the intensity of the grayscale pixel to find the candidate corner. The proposed integration of the Colormap technique and ORB detector method can enhance feature extraction for improving features detection in AR.

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Acknowledgments

This work was supported by Universiti Teknologi Malaysia with grant numbers: R.J130000.7308.4B429,Q.J130000.3051.01 M37, Q.J130000.3008.01 M88, and Fundamental Research Grant (FRGS) by Ministery of Higher Education Malaysia, FRGS/1/2020/ICT10/UTM/01/1, R.J130000.7808.5F368.

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Authors and Affiliations

  1. School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Devi Willieam Anggara

  2. UTM-IRDA Digital Media Centre, Media and Game Innovation of Excellence (MaGICX), Institute of Human Centered Engineering (iHumEn), Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Mohd Shafry Mohd Rahim, Ajune Wanis Ismail & Nor Anita Fairos Ismail

  3. Centre for Internship Training and Academic Enrichment (CITrA), Universiti Malaya, Kuala Lumpur, Malaysia

    Seng Yue Wong

  4. Design Communication Visual, Creative Industries School, Telkom University, Bandung, Indonesia

    Runik Machfiroh, Arif Budiman & Aris Rahmansyah

  5. Department of Electrical Engineering, Universitas Riau, Pekanbaru, Indonesia

    Dahliyusmanto

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  1. Devi Willieam Anggara
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Anggara, D.W., Rahim, M.S.M., Ismail, A.W. et al. Integrated Colormap and ORB detector method for feature extraction approach in augmented reality. Multimed Tools Appl 81, 35713–35729 (2022). https://doi.org/10.1007/s11042-022-13548-x

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