• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.79-87
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• 2015

Surface segmentation and edge feature lines extraction from fractured fragments of relics are essential steps for computer assisted restoration of fragmented relics. As these fragments were heavily eroded, it is a challenging work to segment surface and extract edge feature lines. This paper presents a novel method to segment surface and extract edge feature lines from triangular meshes of irregular fractured fragments. Firstly, a rough surface segmentation is accomplished by using a clustering algorithm based on the vertex normal vector. Secondly, in order to differentiate between original and fracture faces, a novel integral invariant is introduced to compute the surface roughness. Thirdly, an accurate surface segmentation is implemented by merging faces based on face normal vector and roughness. Finally, edge feature lines are extracted based on the surface segmentation. Some experiments are made and analyzed, and the results show that our method can achieve surface segmentation and edge extraction effectively.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.55-61
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• 2021

In this paper, we proposed a DeepLabv3+ based encoder-decoder model utilizing an attention mechanism for precise semantic segmentation. The DeepLabv3+ is a semantic segmentation method based on deep learning and is mainly used in applications such as autonomous vehicles, and infrared image analysis. In the conventional DeepLabv3+, there is little use of the encoder's intermediate feature map in the decoder part, resulting in loss in restoration process. Such restoration loss causes a problem of reducing segmentation accuracy. Therefore, the proposed method firstly minimized the restoration loss by additionally using one intermediate feature map. Furthermore, we fused hierarchically from small feature map in order to effectively utilize this. Finally, we applied an attention mechanism to the decoder to maximize the decoder's ability to converge intermediate feature maps. We evaluated the proposed method on the Cityscapes dataset, which is commonly used for street scene image segmentation research. Experiment results showed that our proposed method improved segmentation results compared to the conventional DeepLabv3+. The proposed method can be used in applications that require high accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.77-80
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• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.368-377
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• 2011

This paper explains the hardware structure of SURF(Speeded Up Robust Feature) based feature point extractor and its FPGA verification result. SURF algorithm produces novel scale- and rotation-invariant feature point and descriptor which can be used for object recognition, creation of panorama image, 3D Image restoration. But the feature point extraction processing takes approximately 7,200msec for VGA-resolution in embedded environment using ARM11(667Mhz) processor and 128Mbytes DDR memory, hence its real-time operation is not guaranteed. We analyzed integral image memory access pattern which is a key component of SURF algorithm to reduce memory access and memory usage to operate in c real-time. We assure feature extraction that using a Vertex-5 FPGA gives 60frame/sec of VGA image at 100Mhz.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.942-947
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• 2003

An important signal processing problem in PVDF sensor is the restoration of surface information from electric sensing signals. The objectives of this research are to design a new texture sensing system and to develop a new signal processing algorithm for signals from the sensor to be tangibly displayed by tangible interface systems. The texture sensing system is designed to get surface information with high resolution and dynamic range. First, a PVDF sensor is made of piezoelectric polymer (polyvinylidene fluoride) strips molded in a silicon rubber and attached in a rigid cylinder body. The sensor is mounted to a scanning system for dynamic sensing. Secondly, a new signal processing algorithm is developed to restore surface information. The algorithm consists of the two-dimensional modeling of the sensor using an identification method and inverse filtering from sensing signals into estimated surface information. Finally the two-dimensional surface information can be experimentally reconstructed from sensing signals using the developed signal processing algorithm.

• Animal cells and systems
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• v.7 no.3
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• pp.197-205
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• 2003

White snakeroot (Ageratina altissima (L.) R. King & H. Robinson) as an invasive alien plant appeared more abundantly at lower elevations where frequent artificial interferences prevailed than at higher elevations where such impacts were less. They appeared abundantly in introduced forests such as black locust plantation but they did not appear or were rare in natural forests such as oak forest. But an exceptional phenomenon where white snakeroot did not appear was found in a Korean pine stand with dense cover afforested recently. Appearance status of white snakeroot in each section of trampling path depended on breadth of the path and relative light intensity. Growth of white snakeroot measured as the number of ramet per genet, height, and biomass was better near the trampling path and was reduced toward the forest interior. The growth was proportionate to the relative light intensity measured according to distance from the trampling path. Such results support the fact generally known in relation invasion and expansion of the invasive alien plants. From this viewpoint, we suggest a management plan that applies ecological restoration principles to address ecosystems infected with white snakeroot by restoring the integral feature of the degraded nature and more thoroughly conserving the remaining nature.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.17-23
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• 1997

A 3-D vision system is developed to evaluate blanks' line up and monitor gap and thickness difference between blanks in tailored blank welding system. A structured lighting method is used for 3-D vision recognition. Images of sheared portion in blanks are irregular according to roughness of blank surface, shape of sheared geometry and blurring. It is difficult to get accurate and reliable informations in the case of using binary image processing or contour detection techniques in real time for such images. We propoe a new energy integration method robust to blurring and changes of illumination. The method is computationally simple, and uses feature restoration concept, different to another digital image restoration methods which aim image itself restoration and may be used in conventional applications using structured line lighting technique. Experimental results show this system measuring repeatability is .+-. pixel for gap and thickness difference in static and dynamic tests. The data are expected to be useful for preview gap control.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1237-1239
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• 1996

3-D object recognition and restoration independent of the translation and rotation using an ultrasonic sensor array, neural networks and invariant moment are presented. Using invariant moment vectors on the acquired $16{\times}8$ pixel data, 3-D objects can be classified by SOFM(Self Organizing Feature Map) neural networks. Invariant moment vectors kept constant independent of the translation and rotation. The experiment result shows the suggested method can be applied to the environment recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12B
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• pp.1051-1059
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• 2003

The key feature of GMPLS is the provision of network resources and the automatic set-up of a path. And the mechanism of protection and restoration of a path is presented when network component fails. This paper suggests CR-LDP Static Detour Mechanism and Dynamic Detour Mechanism. CR-LDP Detours are a mechanism to set up detour paths automatically at every node to protect working path. Hence suggested mechanism performance is compared with existing mechanisms by computer simulation.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.349-352
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• 1994

An object recognition and restoration using ultrasound sensors and neural networks are presented. The planar arrangement of the sensor is used to reduce the interference effects between sensors. The SOFM(Self-Organizing Feature Map) Neural Network and SCL(Simple Competitive Learning) method are learned with the acquired data. Lab experiments were performed that the object can be recognized ed the resolutions of the object can be enhanced by using the small number of the ultrasound array and neural networks.