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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.