• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.270-274
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• 2008

This paper proposes an advanced signal processing circuit for a fingerprint sensor based on ridge resistivity. A novel fingerprint integrated sensor using ridge resistivity variation resulting from ridges and valleys on the fingertip is presented. The pixel level simple detection circuit converts from a small and variable sensing current to binary voltage out effectively. The sensor circuit blocks were designed and simulated in a standard CMOS 0.35 ${\mu}m$ process.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• Journal of Sensor Science and Technology
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• v.14 no.1
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• pp.28-32
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• 2005

In this paper, a CMOS integrated detection circuit for capacitive type fingerprint sensor signal processing is described. We designed a detection circuit of charge-sharing sensing scheme. The proposed detection circuit increases the voltage difference between a ridge and valley. The test chip is composed of $160{\times}192$ array sensing cells (12 by $12.7{\;}mm^{2}$). The chip was fabricated on a 0.35 m standard CMOS process. Measured difference voltage between a ridge and valley was 0.95 V.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.301-304
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• 2011

This paper describes the possibility of a low-power, high-resolution fingerprint sensor chip. A modified capacitive detection circuit of charge sharing scheme is proposed, which reduces the static power dissipation and increases the voltage difference between a ridge and valley more than conventional circuit. The detection circuit is designed and simulated in 3.3V, 0.35${\mu}$m standard CMOS process, 40MHz condition. The result shows about 27% power dissipation reduction and 90% improvement of difference between a ridge and valley sensing voltage. The proposed circuit is more stable and effective than a typical circuit.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.692-695
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• 2011

This paper describes the possibility of a low-power, high-resolution fingerprint sensor chip. A modified capacitive detection circuit of charge sharing scheme is proposed, which reduces the static power dissipation and increases the voltage difference between a ridge and valley more than conventional circuit. The detection circuit is designed and simulated in 3.3V, $0.35{\mu}m$ standard CMOS process, 40MHz condition. The result shows about 35% power dissipation reduction and 90% improvement of difference between a ridge and valley sensing voltage. The proposed circuit is more stable and effective than a typical circuit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.943-949
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• 2000

In object analysis, line and curve finding plays a universal role. And, it can be accomplished by detecting ridges and ravines in digital gray-scale images. In this paper, we present a new method of detecting ridges and ravines by using local min and max operations. This method uses erosion and dilation properties of these fuzzy logic operations and requires no information of ridge or ravine direction, so that the method is simple and easy in comparison with the conventional analytical methods. The experimental results show that the technique has a strong ability in finding ridges and ravines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1740-1747
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• 2004

In this paper, we proposed an effective method for detecting fingerprint ridge direction based on the run-length and chain codes. First, a fingerprint image is normalized, and it is thresholded to obtain binary image with foreground and background regions. The foreground regions is composed of fingerprint ridges, and the ridges is encoded with the run-length and chain codes. To detect directional information, the boundary of ridge codes is traced, and curvature is calculated at ecah point of boundary. And the detected direction value is smoothed with appropriate window locally. The proposed method is applied to NIST and FVC2002 fingerprint database to evaluate performance. By the experimental results, the proposed method can be used to obtain ridge direction value in fingerprint image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.118-126
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• 1996

In object analysis by image processing, finding lines plays a universal role. And these lines can be easily found by detecting ridges and valleys in digital gray scale images. In this paper, a new method of detecting ridges and valleys by using local min/max operations was presented. This method detects ridges and valleys of desired width by using erosion and dilation properties of local min/max operations, and requires no information of ridge or valley direction. Therefore the method is efficient and computationally simple in comparision with the conventional analytical method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1343-1348
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• 2011

A modified capacitive detection circuit of charge sharing scheme is proposed, which reduces the static power dissipation and increases the voltage difference between a ridge and valley more than a conventional circuit. The detection circuit is designed and simulated in 3.3V, $0.35{\mu}m$ standard CMOS process, 40MHz condition. The result shows about 47% power dissipation reduction and 90% improvement of difference between a ridge and valley sensing voltage. The proposed circuit is layout without area increasing of a one pixel.

• ETRI Journal
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• v.28 no.6
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• pp.770-776
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• 2006

This paper presents a hyperspectral imaging technique based on laser-induced fluorescence for non-invasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect image data in a number of narrow, adjacent spectral bands. Such high-resolution measurement of spectral information reveals contiguous emission spectra at each image pixel useful for the characterization of constituent materials. The hyperspectral image data used in this study are fluorescence images of mouse skin consisting of 21 spectral bands in the visible spectrum of the wavelengths ranging from 440 nm to 640 nm. Fluorescence signal is measured with the use of laser excitation at 337 nm. An acousto-optic tunable filter (AOTF) is used to capture images at 10 nm intervals. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the spatial offsets caused by the refraction differences in AOTF at different wavelengths during the image capture procedure. The unique fluorescence spectral signatures demonstrate a good separation to differentiate malignant tumors from normal tissues for rapid detection of skin cancers without biopsy.