• Current Optics and Photonics
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• v.3 no.6
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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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• v.14 no.7
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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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.225-230
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• 2011

In this paper, we propose the segmentation method for detecting the facial region by using watershed based on depth information and merge algorithm. The method consists of three steps: watershed segmentation, seed region detection, and merge. The input color image is segmented into the small uniform regions by watershed. The facial region can be detected by merging the uniform regions with chromaticity and edge constraints. The problem in the existing method using only chromaticity or edge can solved by the proposed method. The computer simulation is performed to evaluate the performance of the proposed method. The simulation results shows that the proposed method is superior to segmentation facial region.