• Nuclear Engineering and Technology
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• v.39 no.4
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• pp.313-326
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• 2007

In this paper, an algorithm to reconstruct two orthogonal images into a three-dimensional image is developed in order to measure the bubble size and volume in a two-phase boiling flow. The central-active contour model originally proposed by P. $Szczypi\'{n}ski$ and P. Strumillo is modified to reduce the dependence on the initial reference point and to increase the contour stability. The modified model is then applied to the algorithm to extract the object boundary. This improved central contour model could be applied to obscure objects using a variable threshold value. The extracted boundaries from each image are merged into a three-dimensional image through the developed algorithm. It is shown that the object reconstructed using the developed algorithm is very similar or identical to the real object. Various values such as volume and surface area are calculated for the reconstructed images and the developed algorithm is qualitatively verified using real images from rubber clay experiments and quantitatively verified by simulation using imaginary images. Finally, the developed algorithm is applied to measure the size and volume of vapor bubbles condensing in a subcooled boiling flow.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1019-1027
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• 2017

As high resolution satellite images can be used, numerous studies have been carried out for exploiting these images in various fields. This paper proposes horse hoof shaped object detection method based on mathematical morphology to extract interesting targets. Interesting targets have conceptually similar shapes such as a horse hoof, not having exact size or shape. Detection of an object with the similar shapes is possible by applying mathematical morphology processes. The proposed method allows an automatic object detection system to detect the meaningful object in a large satellite image rapidly. The mathematical morphology process can be applied to binary images, and thus this method is very simple. Therefore, this method can easily extract a "horse hoof shaped object" from any image that has indistinct edges of the interesting object and different image qualities depending on the filming location, filming time, and filming environment. Using the proposed method by which a "horse hoof shaped object" can be rapidly extracted, the performance of the automatic object detection system can be improved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.387-390
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• 2001

Thermopile thermometer can measure the temperature of an object without attaching the object. It measures the temperature by receiving the radiation energy from objects. The idea of this is from the law of Stefan-Boltzmann. In the past it was not used well because the size was big and the cost was too expensive. But, In these days it can be used many field because the size become smaller and advantage of cost by using micro machine technology. However, The accuracy of measuring is not better than electric type. So we want to improve the accuracy of sensor by analyzing the heat transfer of the thermopile. To analyze temperature distribution in the thermopile sensor, we use the FEM software which is named ANSYS. The conduction and radiation heat transfer is considered to simulate the temperature distribution and time response inside of the sensor.

• Proceeding of KASS Symposium
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• 2005.05a
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• pp.246-253
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algorithm are searching methods for optimum values. The object of this reserch is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic one, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.108-113
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• 2022

The deep-learning-based measurement method with the through-focus scanning optical microscopy (TSOM) estimated the size of the object using the classification. However, the measurement performance of the method depends on the number of subdivided classes, and it is practically difficult to prepare data at regular intervals for training each class. We propose an approach to measure the size of an object in the TSOM image using the deep-learning regression model instead of using classification. We attempted our proposed method to estimate the top critical dimension (TCD) of through silicon via (TSV) holes with 2461 TSOM images and the results were compared with the existing method. As a result of our experiment, the average measurement error of our method was within 30 nm (1σ) which is 1/13.5 of the sampling distance of the applied microscope. Measurement errors decreased by 31% compared to the classification result. This result proves that the proposed method is more effective and practical than the classification method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.903-906
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• 1998

We propose a new method for merging partical regions which have similar motion characteristics. In the proposed method, the trajectories of each partial regions are computed and the regions consisting a same object are merged by a similarity function defined in this paper. The similarity function is defined to take into consideration the motion characteristics of the trajectories. The proposed method shows good performance when the regions of an object show little variation in size and shape.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.573-574
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• 1992

We developed a recognition and tracking system of moving objects. The system consists of one CCD video camera, two DC motors in horizontal and vertical axles with encoders, pluse width modulation(PWM) driving unit, 16 bit NEC 9801 microcomputer, and their interfaces. The recognition and tracking system is able to recognize shape and size of a moving object and is able to track the object within a certain range of errors. This paper presents the brief introduction of the recognition and tracking system developed in our laboratory.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.113-116
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• 2001

In this paper we present a new hierarchical layout object extraction algorithm, which is based on rectangles rather than edges. The original layout data is modeled as instances connected by wires. Each polygon shape is divided into a set of rectangles and the instances and wires are extracted and recognized from those rectangles together with their connection and size information. We have applied the algorithm to actual layouts. Experiments on several standard cell library demonstrate the effectiveness of the algorithm.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.671-678
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• 2005

In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.