• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.398-405
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• 2018

In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.125-132
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• 2008

Omnidirectional camera system with a wide view angle is widely used in surveillance and robotics areas. In general, most of previous studies on estimating a projection model and the extrinsic parameters from the omnidirectional images assume corresponding points previously established among views. This paper presents a novel omnidirectional camera calibration based on automatic contour matching. In the first place, we estimate the initial parameters including translation and rotations by using the epipolar constraint from the matched feature points. After choosing the interested points adjacent to more than two contours, we establish a precise correspondence among the connected contours by using the initial parameters and the active matching windows. The extrinsic parameters of the omnidirectional camera are estimated minimizing the angular errors of the epipolar plane of endpoints and the inverse projected 3D vectors. Experimental results on synthetic and real images demonstrate that the proposed algorithm obtains more precise camera parameters than the previous method.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.37-40
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• 2000

A fast method of Hangul address word verification is presented in this Paper. Pre-segmentation and recognition by DP matching is adopted in this paper. An address line image is over-segmented by analyzing the topology of connected components and the projection profile. A fast individual Hangul character verifier was developed by applying SVM (Support Vector Machine). The segmentation hypothesis was represented by lattice structure, and a best path search by dynamic programming generates the most probable segmentation path and the final verification score. The word verifier was tested on 310 address image DB, and it show the possibility of improvements of this method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.35-44
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• 2007

Since the omnidirectional camera system with a very large field of view could take many information about environment scene from few images, various researches for calibration and 3D reconstruction using omnidirectional image have been presented actively. Most of line segments of man-made objects we projected to the contours by using the omnidirectional camera model. Therefore, the corresponding contours among images sequences would be useful for computing the camera transformations including rotation and translation. This paper presents a novel two step minimization method to estimate the extrinsic parameters of the camera from the corresponding contours. In the first step, coarse camera parameters are estimated by minimizing an angular error function between epipolar planes and back-projected vectors from each corresponding point. Then we can compute the final parameters minimizing a distance error of the projected contours and the actual contours. Simulation results on the synthetic and real images demonstrated that our algorithm can achieve precise contour matching and camera motion estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.288-296
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• 2009

In POCS (projection onto convex sets)-based reconstruction of HR (high resolution) image, the quality of reconstructed image is gradually improved through iterative motion estimation and image restoration. The amount of computation, however, increases because of the repeated inter-frame motion estimation. In this paper, an HR reconstruction algorithm is proposed where modified ARPS (adaptive rood pattern search) and POCS are simultaneously performed. In the modified ARPS, the motion estimates obtained from phase correlation or from the previous steps in POCS restoration are utilized as the initial reference in the motion estimation. Moreover, estimated motion is regularized with reference to the neighboring blocks' motion to enhance the reliability. Computer simulation results show that, when compared to conventional methods which are composed of full search block matching and POCS restoration, the proposed method is about 30 times faster and yet produces HR images of almost equal or better quality.

• Journal of the Optical Society of Korea
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• v.4 no.1
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• pp.66-70
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• 2000

The main problem of image projection on a transmission type holographic screen is color sepa-ration. And it can be overcome by using a long narrow slit type diffuser as a source of the object beam when we record the screen. But that screen is not optimized and so needs changing several conditions. To set up the system many complicate things should be taken into accounted so it is very important to analyze the basic structure by simple concepts and calculations. We designed the system so that recording and projection axis coincide in one line and showed that the analysis of the system is very simple. We did it by a 1st order paraxial approximation calculation and it was good enough to describe the system. The photo-emulsion layer shrinks after processing of the hologram. It induced unsatisfactory color matching at the viewing zone. To overcome this effect, we pre-checked the shrinkage rate of an emulsion layer by experiments and modified the recording set up to compensate for the amount of shrinkage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1151-1156
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• 2013

In this study, to clearly establish the concept of a geometric modeling I apply for the concept of Pushbroom, limited to two-dimensional radiation Locator to provide a three-dimensional information purposes. Respect to the radiation scanner Pushbroom modeling techniques, geometric modeling method was presented introduced to extract three-dimensional information as long as the rotational component of the Gamma-Ray Linear Pushbroom Stereo System, introduced the two-dimensional and three-dimensional spatial information in the matching relation that can be induced. In addition, the pseudo-inverse matrix by using the conventional least-squares method, GCP(Ground Control Point) to demonstrate compliance by calculating the key parameters. Projection transformation matrix is calculated for obtaining three-dimensional information from two-dimensional information can be used as the primary relationship, and through the application of a radiation image matching technology will make it possible to extract three-dimensional information from two-dimensional X-ray imaging.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.55-61
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• 2005

Digital Elevation Model (DEM) generation from remotely sensed imagery is crucial for a variety of mapping applications such as ortho-photo generation, city modeling. High resolution imaging satellites such as SPOT-5, IKONOS, QUICK-BIRD, ORBVIEW constitute an excellent source for efficient and economic generation of DEM data. However, prerequisite knowledge in the areas of sensor modeling, epipolar resampling, and image matching is required to generate DEM from these high resolution satellite imagery. From the above requirements, epipolar resampling emerges as the most important factors. Research attempts in this area are still in high demand and short supply. Another cause that adds to the complication of the problem is that most studies of DEM generation from IKONOS scenes have been based on rational function model. In this paper, we proposed a new methodology for DEM generation from satellite scenes using parallel projection model which is sensor independent, makes it possible for sensor modeling and epipolar resampling by only few control points. The performance and feasibility of the developed methodology is evaluated through real dataset captured by IKONOS.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.143-148
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• 2008

A real-time face detection is to find human faces robustly under the cluttered background free from the effect of occlusion by other objects or various lightening conditions. We propose a face detection system for real-time applications using wavelet decomposition method based on Gabor features. Firstly, skin candidate regions are extracted from the given image by skin color filtering and projection method. Then Gabor-feature based template matching is performed to choose face cadidate from the skin candidate regions. The chosen face candidate region is transformed into 2-level wavelet decomposition images, from which feature vectors are extracted for classification. Based on the extracted feature vectors, the face candidate region is finally classified into either face or nonface class by the Levenberg-Marguardt back-propagation neural network.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.