Self-organizing maps
Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
A new wavelet-based measure of image focus
Pattern Recognition Letters
Machine Vision: Theory, Algorithms, Practicalities
Machine Vision: Theory, Algorithms, Practicalities
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Measure of image sharpness using eigenvalues
Information Sciences: an International Journal
Efficient architectures for 1-D and 2-D lifting-based wavelet transforms
IEEE Transactions on Signal Processing
IEEE Transactions on Consumer Electronics
Enhanced Autofocus Algorithm Using Robust Focus Measure and Fuzzy Reasoning
IEEE Transactions on Circuits and Systems for Video Technology
The Weibull manifold in low-level image processing: An application to automatic image focusing
Image and Vision Computing
A comparison of contrast measurements in passive autofocus systems for low contrast images
Multimedia Tools and Applications
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This paper presents a passive auto-focus camera control system which can easily achieve the function of auto-focus with no necessary of any active component (e.g., infrared or ultrasonic sensor) in comparison with the conventional active focus system. To implement the technique we developed, the hardware system including the adjustable lens with CMOS sensor and servo motor, an 8051 image capture micro-controller, a field programmable gate array (FPGA) sharpness measurement circuit, a pulse width modulation (PWM) controller, and a personal digital assistant (PDA) image displayer was constructed. The discrete wavelet transformation (DWT), the morphology edge enhancement sharpness measurement algorithms, and the self-organizing map (SOM) neural network were used in developing the control mechanism of the system. Compared with other passive auto-focus methods, the method we proposed has the advantages of lower computational complexity and easier hardware implementation.