• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.350-359
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• 2007

In this paper we present a simple, efficient method for detection of sharp digital images. Recently many digital cameras are equipped with various autofocusing functions to help users take well-focused pictures as easily as possible. However, acquired digital pictures can be further degraded by motion, limited contrast, and inappropriate amount of exposure, to name a few. In order to decide whether to process the image or not, or whether to delete it or not, reliable measure of image quality to detect sharp images from blurry ones is needed. This paper presents a blurriness/sharpness measure, and demonstrates its feasibility using extensive experiments. This method is fast and easy to implement, and accurate. Regardless of the detection accuracy, existing measures are computation-intensive. However, the proposed measure in this paper is not demanding in computation time. Needless to say, this measure can be used for various imaging applications including autofocusing and astigmatism correction.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• Korean Journal of Optics and Photonics
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• v.15 no.6
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• pp.583-590
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• 2004

The autofocus is one of the important processes in the automated vision inspection or measurements using optical microscopes, because it influences the measuring accuracy. In this paper, we used the confocal microscope configuration based on not a pinhole but a single-mode optical fiber. A single mode fiber has the functions of source and detector by applying the reciprocal scheme. As a result, we acquired a simple system configuration and easy alignment of the optical axis. Also, we embodied a fast autofocus system by acquiring the focus error signal through a source modulation technique. The source modulation technique can effectively reduce physical disturbances compared with objective lens modulation, and it is easily applicable to general optical microscopes. The focus error signal was measured with respect to the modulation amplitude, reflectance of the specimen and inclination angle of the measuring surface. The performance of the proposed autofocus system was verified through autofocusing flat mirror surface. In addition, we confirmed that source modulation rarely degrades the depth resolution by the comparison between the FWHMs of axial response curves.