Image Processing Using OpenCV Technique for Real World Data

Author:

Suresh H. S.,Niranjanamurthy M.

Publisher

Springer International Publishing

Reference12 articles.

1. Kumar S., & SaiLavanya, G. V. R. (2020). Face recognition using OpenCV with deep learning. In Kumar, A., Paprzycki, M., & Gunjan V. (Eds.), ICDSMLA 2019. Lecture Notes in Electrical Engineering (Vol. 601). Singapore: Springer. https://doi.org/10.1007/978-981-15-1420-3_122.

2. Thakur, A., Prakash, A., Mishra, A. K., Goldar, A., & Sonkar, A. (2020). Facial recognition with OpenCV. In Smys, S., Tavares, J., Balas, V., & Iliyasu A. (Eds.), Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing (vol 1108). Cham: Springer. https://doi.org/10.1007/978-3-030-37218-7_24.

3. Gayathri Devi, T., Neelamegam P., & Sudha, S. (2017). Image processing system for automatic segmentation and yield prediction of fruits using OpenCV. In 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC) (pp. 758–762). Mysore, 2017. https://doi.org/10.1109/ctceec.2017.8455137.

4. Kaur, B., Jindal, S., & Jindal, S. (2014). An implementation of feature extraction over medical images on OpenCV environment. In 2014 International Conference on Devices, Circuits and Communications (ICDCCom) (pp. 1–6). Ranchi, 2014. https://doi.org/10.1109/icdccom.2014.7024695.

5. Pramkeaw, P. (2016). The study analysis knee angle of color set detection using image processing technique. In 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (pp. 657–660). Naples, 2016. https://doi.org/10.1109/sitis.2016.109.

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