Robust CMOS camera module lens calibration by support vector machine regression

Chan-Yun Yang; Gene Eu Jan; Yung-Yuan Chen

doi:10.1117/12.2014433

31 January 2013 Robust CMOS camera module lens calibration by support vector machine regression

Chan-Yun Yang, Gene Eu Jan, Yung-Yuan Chen

Proceedings Volume 8759, Eighth International Symposium on Precision Engineering Measurement and Instrumentation; 875949 (2013) https://doi.org/10.1117/12.2014433
Event: International Symposium on Precision Engineering Measurement and Instrumentation 2012, 2012, Chengdu, China

Abstract

Motivated by the powerful computational capability in the emerging hardware, an applicable paradigm with its embedded lens calibrator is proposed. The proposed new paradigm for the relationship between the image provider and the image processor shows both the functional and economical merits. The paper first focuses on the developed of the embedded lens calibrator. An underlying support vector machine base regression (SVR) is hence employed as the key to achieve the goal. Based on the structural risk minimization, the SVR, employed as the calibration regressor, simultaneously minimize both the model complexity and empirical error, and create an estimator with a wide margin. The wide margin in regression represents a smooth approximation function for the lens calibration in which variances commonly existed in the CMOS camera modules can tolerably be eliminated. The variance tolerability achieves the calibration function a high robustness, and would conduct potentially the success of the proposed paradigm.

Citation Download Citation

Chan-Yun Yang, Gene Eu Jan, and Yung-Yuan Chen "Robust CMOS camera module lens calibration by support vector machine regression", Proc. SPIE 8759, Eighth International Symposium on Precision Engineering Measurement and Instrumentation, 875949 (31 January 2013); https://doi.org/10.1117/12.2014433

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KEYWORDS

Calibration

Distortion

CMOS cameras

Image processing

Cameras

Data modeling

Manufacturing

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