• Current Optics and Photonics
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• 제3권6호
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• pp.571-576
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• 2019

The morphological changes of anthracnose (fungus) -infected tomato seeds have been studied to identify the infection and characterize its effect. Full-field optical coherence tomography (FF-OCT) has been utilized as a nondestructive but efficient modality for visualizing the effects of fungal infection. The cross-sectional images extracted from a stack of en face FF-OCT images showed significant changes with infection in the seed structure. First of all, the seed coat disappeared with the infection. The thickness of the seed coat of a healthy seed was measured as 28.2 ㎛, with a standard deviation of 1.2 ㎛. However, for infected seeds the gap between surface and endosperm was not appreciably observed. In addition, the measurements confirmed that the dryness of seeds did not affect the internal seed structure. The reconstructed three-dimensional (3D) image revealed that the permeability of the seed coat, which plays the vital role of protecting the seed, is also affected by the infection. These results suggest that FF-OCT has good potential for the identification of fungus-infected tomato seeds, and for many other tasks in agriculture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2919-2937
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• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

• 한국정보전자통신기술학회논문지
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• 제4권4호
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• pp.225-230
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• 2011

본 논문에서는 깊이정보에 기반한 watershed와 영역병합 알고리즘을 이용한 얼굴영역 분할 방법을 제안하였다. 얼굴영역 검출은 영역 분할 단계, 초기 화소 영역 검출 단계, 영역 병합의 세 단계로 구성된다. 입력된 컬러 영상은 제안된 알고리즘에 의해 균일한 작은 영역들로 분할된다. 색도정보와 에지 구속 조건을 사용하여 균일한 영역들을 결합함으로써 얼굴영역을 검출한다. 제안한 알고리즘은 색도정보나 에지정보만을 사용하는 기존 방법에서의 문제점을 해결하였다. 제안한 알고리즘의 성능을 평가하기 위해 컴퓨터 시뮬레이션을 하였으며 정확한 얼굴 영역을 분할할 수 있었다.