• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1890-1900
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• 2017

Tangram game consists of seven pieces of polygons such as triangle, square, and parallelogram. Typical methods of image processing for object recognition may suffer from the existence of side thickness and shadow of the puzzle pieces that are dependent on the pose of 3D-shaped puzzle pieces and the direction of light sources. In this paper, we propose an image processing method that recognizes simple convex polygon-shaped objects irrespective of thickness and pose of puzzle objects. Our key algorithm to remove the thick side of piece of puzzle objects is based on morphological operations followed by logical operations with edge image and background image. By using the proposed object recognition method, we are able to implement a stable tangram game applications designed for tablet computers with front camera. As the experimental results, recognition rate is about 86 percent and recognition time is about 1ms on average. It shows the proposed algorithm is fast and accurate to recognize tangram blocks.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.66-69
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• 2001

Effect of $N_2$ flow rate on properties of GaN thin films grown by plasma-enhanced molecular beam epitaxy(PEMBE) was discussed to optimize the quality of thin films. It was found that at low $N_2$ flow rate indicating high III/V flux ratio, the growth rate of GaN thin films was controlled by $N_2$ flux, and at high $N_2$ flow rate the growth rate was not controlled by $N_2$ flux any longer. It was also found that III/V flux ratio affected film quality. The film grown at higher $N_2$ flow rate showed low background carrier concentration, higher carrier mobility, and narrow FWHM in band-edge emission of low temperature PL. It is thought that the film in more Ga flux region was grown by 2-dimensional layer-by-layer growth mode, and the film in more nitrogen region was grown by 3-D island growth mode. All samples exhibited a good crystallinity.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.236-248
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• 1998

Human observers perceive a contour where no line or edge is given, such as the border between gratings of thin lines offset by half a cycle. Illusory contours occur in a wide variety of circumstances in nature. A common factor in all such figures is the perception of a surface or contour occluding part of a background, i.e. illusory contours are always accompanied by illusory surfaces. Some examples about these kinds of figures are given by Kanizsa's triangle or square. In this paper, we proposed a neural network model for forming(extracting) the illusory surfaces, based on the mechanism of feature extraction found in a mammals' visual pathway. It will be shown that the model can extract the illusory surfaces from illusory contours successfully.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.41
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• pp.21.1-21.3
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• 2019

Background: Treatment planning the correction of a transverse maxillary occlusal plane cant often involves a degree of qualitative "eyeballing", with the attendant possibility of error in the estimated judgement. A simple chair side technique permits quantification of the extent of asymmetry and thereby quantitative measurements for the correction of the occlusal plane cant. Methods: A measuring instrument may be constructed by soldering the edge of a stainless steel dental ruler at 90° to the flat surface of a similar ruler. With the patient either standing in natural head position, or alternatively seated upright in the dental chair, and a dental photographic retractor in situ, the flat under-surface of the horizontal part of this measuring instrument is placed on a unilateral segment of a bilateral structure, e.g. the higher maxillary canine orthodontic bracket hook. The vertical ruler is held next to the contralateral canine tooth, and the vertical distance measured directly from the canine bracket to the flat under-surface of the horizontal part of the measuring instrument. Results: This vertical distance quantifies the overall extent of movement required to level the maxillary occlusal plane. Conclusions: This measuring instrument and simple chair side technique helps to quantify the overall extent of surgical levelling required and may be a useful additional technique in our clinical diagnostic armamentarium.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.5
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• pp.42-51
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection, especially active shadows resulted from moving vehicles. In this paper, a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98% in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic parameters concerning traffic flow is obtained to describe the load of each lane.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.1047-1054
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• 2004

Internal defects in the glass, like-as micro-voids, micro-cracks, or inclusions, easily cause the failure when the glass is exposed to the shock or the thermal variation. In order to produce the highly reliable glass product, the precision inspection of the defect in the glass is required. For this purpose, this paper proposes a machine vision technique based on the auto-focusing method, which searches the defect and measures the location under the fact that the edge image of defect must be the most clear when the focal plane of CCD camera is coincided with the defect. As for the search index, the gradient indicator is presented. The basic principles are verified through the simulations for the computer-generated defect images, where the affects of defect shape, gray level of background, and the brightness of the defect image are also analyzed. Finally, experimental results for actual glass specimens are shown to confirm the applicability of this method to the actual field.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.163-171
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• 2016

Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.85-91
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• 2004

The use of gestures provides an attractive alternate to cumbersome interface devices for human-computer interaction. This has motivated a very active research area concerned with computer vision-based analysis and interpretation of hand gestures The most important issues in gesture recognition are the simplification of algorithm and the reduction of processing time. The mathematical morphology based on geometrical set theory is best used to perform the processing. The key idea of proposed algorithm is to track a trajectory of center points in primitive elements extracted by morphological shape decomposition. The trajectory of morphological center points includes the information on shape orientation. Based on this characteristic we proposed the morphological gesture sequence recognition algorithm using feature vectors calculated to the trajectory of morphological center points. Through the experiment, we demonstrated the efficiency of proposed algorithm.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.502-504
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• 1995

In video image compression, it is important to extract the exact notion information from image sequence in order to perform the data compression, the field rate conversion, and the motion compensated interpolation effectively. It is well known that the location of the smallest sum of absolute difference(SAD) does not always give the true motion vector(MV) since the MV obtained via full block search is often corrupted by noise. In this paper, we first classifies the input blocks into 3 categories : the background, the shade-motion, and the edge-motion. According to the characteristics of the classified blocks, multiple locations of relatively small SAD are searched with an adaptive search window by using the proposed method. The proposed method picks MVs among those candidates by using temporal correlation. Since temporal correlation reveals the noise level in a particular region of the video image sequence, we are able to reduce the search are very effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.633-637
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• 2001

In this paper, we proposed model creation algorithm for multiple moving objects tracking. The proposed algorithm is divided that the initial model creation step as moving objects are entered into background image and the model reformation step in the moving objects tracking step. In the initial model creation step, the initial model is created by AND operating division image, divided using difference image and clustering method, and edge image of the current image. In the model reformation step, a new model was reformed in the every frame to adapt appearance change of moving objects using Hausdorff Distance and 2D-Logarithmic searching algorithm. We simulated for driving cart in the road. In the result, model was created over 98% in case of irregular approach direction of cars and tracking objects number.