• Smart Media Journal
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• v.5 no.1
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• pp.15-23
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• 2016

This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1686-1691
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• 2004

In this paper, we present an improved method to calculate Euclidean distance transform based on Guan's method. Compared to the conventional method, Euclidean distance can be computed faster using Guan's method when the number of feature pixels is small; however, overall computational cost increases proportional to the number of feature pixels in an image. To overcome this problem, we divide feature pixels into two groups: boundary feature pixels (BFPs) and non-boundary feature pixels (NFPs). Here BFPs are defined as those in the 4-neighborhood of foreground pixels. Then, only BFPs are used to calculate the Voronoi diagram resulting in a Euclidean distance map. Experimental results indicate that the proposed method takes 40 Percent less computing time on average than Guan's method. To prove the performance of the proposed method, the computing time of Euclidean distance map by proposed method is compared with the computing time of Guan's method in 16 images that are binary and the size of 512${\times}$512.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.163-172
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• 2010

The free viewpoint video delivers an active contents where users can see the images rendered from the viewpoints chosen by them. Its applications are found in broad areas, especially museum tour, entertainment and so forth. As a new free-viewpoint application, this paper presents a stereoscopic free-viewpoint TIP (Tour Into Picture) where users can navigate the inside of a single image controlling a virtual camera and utilizing depth data. Unlike conventional TIP methods providing 2D image or video, our proposed method can provide users with 3D stereoscopic and free-viewpoint contents. Navigating a picture with stereoscopic viewing can deliver more realistic and immersive perception. The method uses semi-automatic processing to make foreground mask, background image, and depth map. The second step is to navigate the single picture and to obtain rendered images by perspective projection. For the free-viewpoint viewing, a virtual camera whose operations include translation, rotation, look-around, and zooming is operated. In experiments, the proposed method was tested eth 'Danopungjun' that is one of famous paintings made in Chosun Dynasty. The free-viewpoint software is developed based on MFC Visual C++ and OpenGL libraries.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Archives of design research
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• v.19 no.1 s.63
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• pp.225-234
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• 2006

Product designers sketch various ideas of foreground figures(detail design) onto background figures(basic form) and evaluate numerous combinations of them in the late stages of design process. Designers have to test their ideas elaborately with a high-fidelity physical model that looks like a real product. However, due to the requirements of time and expense in making high-fidelity design models, it is impossible to evaluate such a number of combinatorial solutions of background and foreground figures. Contrary to digital models, physical design models are not easily modifiable and so designers cannot easily develope ideas through iterative design-evaluation process. To address these problems, we proposed a new concept 'Augmented Plasticity' that gives morphological editability to a rigid physical object using Augmented Reality technology and implemented the idea as Digital Skin system. Digital Skin system figures out the position and orientation of object surface with ARToolKit visual marker and superimposes a deformed surface image seamlessly using differential rendering method. We tried to apply Digital Skin system to detail design, redesign of product, and material exploration task. In consequence, it was found that Digital Skin system has potential to allow designers to implement and test their ideas very efficiently in the late stages of design process.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.620-624
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• 2009

In this paper, we present a new camera system combining a high-quality 3-D scanner and hybrid camera system to generate a multiview video-plus-depth. In order to get the 3-D video using the hybrid camera system and 3-D scanner, we first obtain depth information for background region from the 3-D scanner. Then, we get the depth map for foreground area from the hybrid camera system. Initial depths of each view image are estimated by performing 3-D warping with the depth information. Thereafter, multiview depth estimation using the initial depths is carried out to get each view initial disparity map. We correct the initial disparity map using a belief propagation algorithm so that we can generate the high-quality multiview disparity map. Finally, we refine depths of the foreground boundary using extracted edge information. Experimental results show that the proposed depth maps generation method produces a 3-D video with more accurate multiview depths and supports more natural 3-D views than the previous works.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.49-55
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• 2007

To improved the multi-resolution fast hierarchical motion estimation by using de-interlacing algorithm that is effective in term of both performance and VLSI implementation, is proposed so as to cover large search area field-based as well as frame based image processing in SoC design. In this paper, we have simulated a various picture mode M=2 or M=3. As a results, the proposed algorithm achieved the motion estimation performance PSNR compare with the full search block matching algorithm, the average performance degradation reached to -0.7dB, which did not affect on the subjective quality of reconstructed images at all. And acquiring the more desirable to adopt design SoC for the fast hierarchical motion estimation, we exploit foreground and background search algorithm (FBSA) base on the dual arithmetic processor element(DAPE). It is possible to estimate the large search area motion displacement using a half of number PE in general operation methods. And the proposed architecture of MHME improve the VLSI design hardware through the proposed FBSA structure with DAPE to remove the local memory. The proposed FBSA which use bit array processing in search area can improve structure as like multiple processor array unit(MPAU).

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.95-104
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• 2012

Pattern recognition using ensemble classifiers is composed of strong classifier which consists of many weak classifiers. In this paper, we used feature extraction to organize strong classifier using static camera sequence. The strong classifier is made of weak classifiers which considers environmental factors. So the strong classifier overcomes environmental effect. Proposed method uses binary foreground image by frame difference method and the boosting is used to train crowdedness model and recognize crowdedness using features. Combination of weak classifiers makes strong ensemble classifier. The classifier could make use of potential features from the environment such as shadow and reflection. We tested the proposed system with road sequence and subway platform sequence which are included in "AVSS 2007" sequence. The result shows good accuracy and efficiency on complex environment.