• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.290-295
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• 1999

Lineament extraction from mountain area often provides valuable geological information. In many cases, the lineaments correspond to a series of continuous large valleys. This paper introduces a new lineament extraction method from Digital Elevation Model (DEM) using Raindrop Tracing Algorithm (RTA). The main advantage of this algorithm over conventional Segment Tracing Algorithm (STA) is that it utilizes DEM directly unlike the STA Which utilizes the shaded relief of DEM. The RTA simulates the real life of raindrops that converge into a large valley. The simulation has been done by sprinkling the randomized raindrops over DEM and counting the number of raindrop path that follows the negative gradient of the DEM. The large counting number indicates the location of a big valley where the raindrops converge. With the help of the counting number array (accumulator array) recording the flowing path information, RTA can produce perfectly unbiased binary image of the lineament.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.24-29
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• 2016

One of the main applications of digital image processing is the estimation of the number of certain types of objects (cells, seeds, peoples etc.) in an image. Difficulties of these counting problems depends on various factors including shape and size variation, degree of object clustering, contrast between object and background, object texture and its variation, and so on. In this paper, a new automatic colony counting algorithm is proposed. We focused on the two applications: counting the bacteria colonies on the agar plate and estimating the number of seeds from images captured by smartphone camera. To overcome the shape and size variations of the colonies, we adopted the distance transformation and peak detection approach. To estimate the reference size of the colony robustly, we also used k-means clustering algorithm. Experimental results show that our method works well in real world applications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.250-255
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• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

• Journal of the Health Care and Life Science
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• v.8 no.2
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• pp.121-125
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• 2020

People counting has always been a method of interest for maximizing energy saving by identifying the congestion level or amount of use of a specific facility to efficiently manage the facility, or automatically implementing a power saving function by identifying the number of people entering and exiting a specific place such as a toilet. The method of counting people by image processing is very expensive and has the disadvantage of being severely affected by the surrounding environment of the lighting. In the case of the area sensor, there is a disadvantage of counting as one person when the number of people passes close with arms folded. In order to solve the existing method, which is expensive, affected by lighting, or inaccurate the number of people in certain cases, this paper proposes a new method of counting people using the principle of LiADAR. Accurate counting of the number of people entering the hospital will help manage hospital facilities, but it will also help to establish effective quarantine measures at the present time when Corona 19 is prevalent.

• Child Studies in Asia-Pacific Contexts
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• v.5 no.1
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• pp.39-49
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• 2015

Not all parents are skilled in scaffolding their young children's numeracy learning. The present study investigated the effectiveness of a parent training program in promoting Filipino young children's number sense via card game playing at home. Participants were 161 young children and their parents; families were of a relatively low socioeconomic status. During the 10-week intervention period, parents in the experimental group received training on how to use number game cards to help their children acquire various numeracy concepts; parents in the control group received no special instructions. Children in the experimental group showed greater improvements in their performance on six number sense tasks (namely numeral identification, object counting, rote counting, missing number, numerical magnitude comparison, and addition) over the intervention period than did children in the control group. Findings of the present study suggest that providing simple training to parents on strategies for fostering their young children's number sense at home is important for giving children a good early start in basic number knowledge.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.97-105
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• 1998

The fiber oriented condition inside fiber reinforced composite material is a basic factor of mechanical properties of composite materials. It is very important to meausure the fiber orientation angle for the determination of molding conditions, mechanical characteristics, and the design of composite materials. In the work, the fiber orientation distribution of simulation figure plotted by PC is measured using image processing in order to examine the accuracy of intersection counting method. The fiber orientation function measured by intersection counting method using image processing is compared with the calculated fiber orientation function. The results show that the measured value of fiber orientation function using intersection counting method is lower than the calculated value, because the number of intersection between the scanning line and the fiber with smaller fiber aspect ratio is counted less than with larger fiber aspect ratio.

• Journal of the Optical Society of Korea
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• v.12 no.2
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• pp.88-92
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• 2008

This paper discusses a photon-counting linear discriminant analysis (LDA) with computational integral imaging (II). The computational II method reconstructs three-dimensional (3D) objects on the reconstruction planes located at arbitrary depth-levels. A maximum likelihood estimation (MLE) can be used to estimate the Poisson parameters of photon counts in the reconstruction space. The photon-counting LDA combined with the computational II method is developed in order to classify partially occluded objects with photon-limited images. Unknown targets are classified with the estimated Poisson parameters while reconstructed irradiance images are trained. It is shown that a low number of photons are sufficient to classify occluded objects with the proposed method.

• Journal of the Optical Society of Korea
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• v.20 no.5
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• pp.579-585
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• 2016

Integral imaging combined with photon-counting detection has been researched for three-dimensional information sensing under low-light-level conditions. This paper addresses the extraction of distance information with photon-counting integral imaging. The longitudinal distance to the object is obtained utilizing photon-counting elemental images. The pixel disparity is estimated by maximizing the nonlinear correlation of photocounts. The first- and second-order statistical properties of the nonlinear correlation are theoretically derived. In the experiments, these properties are verified by varying the mean number of photocounts in the scene. The average distance is compared to that from the intensity information, showing the robustness of the proposed system even at low photocounts.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.113-119
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• 2020

This study proposed the structure of the cluster's cell counting algorithm for cell analysis. The image required for cell count is taken under a microscope. At present, the cell counting algorithm is reported to have a problem of low accuracy of results due to uneven shape and size clusters. To solve these problems, the proposed algorithm has a feature of calculating the number of cells in a cluster by applying a radius change analysis to the existing distance conversion and watershed algorithm. Later, cell counting algorithms are expected to yield reliable results if applied to the required field.

• Journal of Microbiology and Biotechnology
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• v.8 no.2
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• pp.182-184
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• 1998

PCR was used for quantitative counting of Bifidobacterium spp. in a sample mixed with Lactobacillus acidophilus using two primer sets; one set for universal priming and the other set for Bifidobacterium specific priming. DNA products from two independent PCRs with DNA extracted from the mixed sample were found to be easily distinguishable from each other by agarose gel electrophoresis. The concentrations of PCR products correlated with the total number of bacteria and with the number of Bifidobacterium spp. present in the sample.