• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1213-1218
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• 2018

Recently introduced Mask R - CNN presents a conceptually simple, flexible, general framework for instance segmentation of objects. In this paper, we propose an algorithm for efficiently searching objects of images, while creating a segmentation mask of heat generation part for an instance which is a heating element in a heat sensed image acquired from a thermal infrared camera. This method called a mask R - CNN is an algorithm that extends Faster R - CNN by adding a branch for predicting an object mask in parallel with an existing branch for recognition of a bounding box. The mask R - CNN is added to the high - speed R - CNN which training is easy and fast to execute. Also, it is easy to generalize the mask R - CNN to other tasks. In this research, we propose an infrared image detection algorithm based on R - CNN and detect heating elements which can not be distinguished by RGB images. As a result of the experiment, a heat-generating object which can not be discriminated from Mask R-CNN was detected normally.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.113-121
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• 1989

A software interface called CGI-K including device driver routines and graphics primitives for the grphic board "K" was designed, implemented in the Design Automation Laboratory of KAIST and installed on IBM PC/AT, using assembly and C language supported by TMS 34010 grphics processor. Several algorithms generating the graphics primitives such as box, circle, pie chord are proposed. The drawing speed of CGI-K on the graphic board K was found out to be three to ten times faster than that of the EGA for several examples. A 2-D graphics editor called GRIM (graphics input and modification) and a 3-dimensional graphics renderer called IPCHE which can draw 3-D objects were developed as two major application programs running on CGI-K. The graphics primitives supported in GRIM include polygon, box, circle, and ace. The IPCHE receives a 3-D objects data file and displays the 3-D object on the screen with hidden surface removal, shading, and perspective scaling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.732-737
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• 2005

Distal 3D Real Object Duplication System(RODS) consists of 3D Scanner and Solid Freeform Fabrication System(SFFS). It is a device to make three-dimensional objects directly from the drawing or the scanning data. In this research, we developed an office type SFFS based on Three Dimensional Printing Process and a industrial SFFS using Dual Laser. An office type SFFS applied sliding mode control with sliding perturbation observer(SMCSPO) algorithm for control of this system. And we measured process variables about droplet diameter measurement and powder bed formation etc. through experiments. Also, in order to develop more elaborate and speedy system for large objects than existing SLS process, this study applies a new Selective Multi-Laser Sintering(SMLS) process and 3-axis dynamic Focusing Scanner for scanning large area instead of the existing $f\theta$ lens. In this process, the temperature has a great influence on sintering of the polymer. Also the laser parameters are considered like that laser beam power, scan speed, scan spacing. Now, this study is in progress to eveluate the effect of experimental parameters on the sintering process.

• Journal of the Korea Computer Graphics Society
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• v.25 no.5
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• pp.11-20
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• 2019

With the development of deep learning technology, research is being actively carried out on user-friendly interfaces that are suitable for use in virtual reality or augmented reality applications. To support the interface using the user's hands, this paper proposes a deep learning-based fingertip detection method to enable the tracking of fingertip coordinates to select virtual objects, or to write or draw in the air. After cutting the approximate part of the corresponding fingertip object from the input image with the Grad-CAM, and perform the convolution neural network with Atrous Convolution for the cut image to detect fingertip location. This method is simpler and easier to implement than existing object detection algorithms without requiring a pre-processing for annotating objects. To verify this method we implemented an air writing application and showed that the recognition rate of 81% and the speed of 76 ms were able to write smoothly without delay in the air, making it possible to utilize the application in real time.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1263-1268
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• 2018

In this paper, a video analysis is proposed to implement video surveillance system with deep learning object detection and probabilistic data association filter for tracking multiple objects, and suggests its implementation using GPU. The proposed video analysis technique involves object detection and object tracking sequentially. The deep learning network architecture uses ResNet for object detection and applies probabilistic data association filter for multiple objects tracking. The proposed video analysis technique can be used to detect intruders illegally trespassing any restricted area or to count the number of people entering a specified area. As a results of simulations and experiments, 48 channels of videos can be analyzed at a speed of about 27 fps and real-time video analysis is possible through RTSP protocol.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.695-698
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• 2014

As most the scanning systems developed until now provide radiation scan plane images of the inspected objects, there has been a limitation in judging exactly the shape of the objects inside a logistics container exactly with only 2-D radiation image information. Two 2-dimensional radiation images which have different disparity values are acquired from a newly designed stereo image acquisition system which has one additional line sensor to the conventional system. Using a matching algorithm the 3D reconstruction process which find the correspondence between the images is progressed. In this paper, we proposed a new volume based 3D reconstruction algorithm and experimental results show the proposed new volume based reconstruction technique can provide more efficient visualization for cargo inspection. The proposed technique can be used for the development of the high speed and more efficient non-destructive auto inspection system.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.272-277
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• 2010

AR(Augmented Reality) needs medium between real and virtual, world, and recognition techniques are necessary to track an object continuously. Optical tracking using marker is mainly used, but it takes time and is inconvenient to attach marker onto the target objects. Therefore, many researchers try to develop markerless tracking techniques nowaday. In this paper, we extract features and 3D position from 3D objects and suggest realtime tracking based on these features and positions, which do not use just coplanar features and 2D position. We extract features using SURF, get rotation matrix and translation vector of 3D object using POSIT with these features and track the object in real time. If the extracted features are nor enough and it fail to track the object, then new features are extracted and re-matched to recover the tracking. Also, we get rotation in matrix and translation vector of 3D object using POSIT and track the object in real time.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.13-19
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• 2011

In this paper, a visual surveillance system using SOPC based NIOS II embedded processor and C2H compiler was implemented. In this system, the IP is constructed by C2H compiler for the output of the camera images, image processing, serial communication and network communication, then, it is implemented to effectively control each IP based on the SOPC and the NIOS II embedded processor. And, an algorithm which updates the background images for high speed and robust detection of the moving objects is proposed using the Adaptive Gaussian Mixture Model(AGMM). In results, it can detecte the moving objects(pedestrians and vehicles) under day-time and night-time. It is confirmed that the proposed AGMM algorithm has better performance than the Adaptive Threshold Method(ATM) and the Gaussian Mixture Model(GMM) from our experiments.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.167-175
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• 2002

Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.439-449
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• 2005

Distributed main memory database management systems (DMM-DBMSs) store the database in main memories of the participating sites. They provide high performance through fast access to the local databases and high speed communication among the sites. Recently, a lot of research results on DMM- DBMSs has been reported. However, to the best of our knowledge, there is no known research result on the performance of the catalog management schemes for DMM-DBMSs. In this work, we evaluated the performance of the partitioned catalog management schemes through experimental analysis. First, we classified the partitioned catalog management schemes into three categories : Partitioned Catalogs Without Caching (PCWC), Partitioned Catalogs With Incremental Caching (PCWIC), and Partitioned Catalogs With Full Caching (PCWFC). Experiments were conducted by varying the number of sites, the number of terminals per site, buffer size, write query ratio, and local query ratio. Experiments show that PCWFC outperforms the other two schemes in all cases. It also means that the performance of PCWIC gradually increases as time goes by. It should be noted that PCWFC does not guarantee high performance for disk-based distributed DBMSs in cases when the workload of individual site is high, catalog write ratio is high, or remote data objects are accessed very frequently. Main reason that PCWFC outperforms for DMM-DBMSs is that query compilation and remote catalog access can be done in a very high speed, even when the catalogs of the remote data objects are frequently updated.