• International journal of advanced smart convergence
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• v.6 no.4
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• pp.88-95
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• 2017

The conventional scan methods are based on a laser scanner and a depth camera, which requires high cost and complicated post-processing. Whereas in photometric scanning method, the 3D modeling data is acquired through multi-view images. This is advantageous compared to the other methods. The quality of a photometric 3D model depends on the environmental conditions or the object characteristics, but the quality is lower as compared to other methods. Therefore, various methods for improving the quality of photometric scanning are being studied. In this paper, we aim to investigate the effect of illumination conditions on the quality of photometric scanning data. To do this, 'Moai' statue is 3D printed with a size of $600(H){\times}1,000(V){\times}600(D)$. The printed object is photographed under the hard light and soft light environments. We obtained the modeling data by photometric scanning method and compared it with the ground truth of 'Moai'. The 'Point-to-Point' method used to analyseanalyze the modeling data using open source tool 'CloudCompare'. As a result of comparison, it is confirmed that the standard deviation value of the 3D model generated under the soft light is 0.090686 and the standard deviation value of the 3D model generated under the hard light is 0.039954. This proves that the higher quality 3D modeling data can be obtained in a hard light environment. The results of this paper are expected to be applied for the acquisition of high-quality data.

• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.96-102
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• 2012

This paper addresses photometric distortion problems of a compact 3D scanning sensor which is composed of a micro-size and inexpensive camera-projector system. Recently, many micro-size cameras and projectors are available. However, erroneous 3D scanning results may arise due to the poor and nonlinear photometric properties of the sensors. This paper solves two inherent photometric distortions of the sensors. First, the response functions of both the camera and projector are derived from the least squares solutions of passive and active calibration, respectively. Second, vignetting correction of the vision camera is done by using a conventional method, however the projector vignetting is corrected by using the planar homography between the image planes of the projector and camera, respectively. Experimental results show that the proposed technique enhances the linear properties of the phase patterns that are generated by the sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.219-226
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• 2013

A distortion correction technique is presented to enhance the 3D scanning performance of a micro-size camera-projector system. Recently, several types of micro-size digital projectors and cameras are available. However, there have been few effort to develop a micro-size 3D scanning system. We develop a micro-sized 3D scanning system which is based on the structured light technique. Three images of phase-shifted sinusoidal patterns are projected, captured, and analyzed by the system to reconstruct 3D shapes of very small objects. To overcome inherent optical imperfection of the micro 3D sensor, we correct the vignetting and blooming effects which cause distortions in the phase image. Error analysis and 3D scanning results on small real objects are presented to show the performance of the developed 3D scanning system.

• 한국생물공학회:학술대회논문집
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• 2005.04a
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• pp.120-122
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• 2005

Phospholipases C (PLCs) from B. cereus 318 and recombinant Pichia pastoris were immobilized on sol-gel coated glass beads. The pH and temperature on immobilized PLC activity were investigated. Operational and storage stability of the immobilized PLCs was measured by spectro- photometric assay. The PLCs immobilized on sol-gel coated glass beads were photographed by scanning electron microscope (SEM).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1127-1127
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• 2001

The transfer of predictive models using various chemometric techniques has been reported for FTNIR and scanning-grating based NIR instruments with respect relatively dry samples (<10% water). Some of the currently used transfer techniques include slope and bias correction (SBC), direct standardization (DS), piecewise direct standardization (PDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT) and application of neural networks. In a previous study (Greensill et at., 2001) on calibration transfer for wet samples (intact melons) across silicon diode array instrumentation, we reported on the performance of various techniques (SBC, DS, PDS, double window PDS (DWPDS), OSC, FIR, WT, a simple photometric response correction and wavelength interpolative method and a model updating method) in terms of RMSEP and Fearns criterion for comparison of RMSEP. In the current study, we compare these melon transfer results to a similar study employing pairs of spectrometers for non-invasive prediction of soluble solid content of peaches.