• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.43 no.6 s.312
• /
• pp.68-75
• /
• 2006

During cancer therapy by using high energy radiation, it is possible to improve the radiation therapy efficiency by performing a precise radiation therapy after verification of generated setup errors. In this paper, the video based electronic portal imaging device (EPID) which could display the portal image with near real time was developed to verify treatment position errors in radiation therapy instead of an analog typed portal film. This EPID system for applying QA tool of radiation therapy machine was consisted of a metal/fluorescent screen, $45^{\circ}$mirror, camera and image grabber. Radiation field verification has been performed to check quality assurance of the treatment machine itself by using this EPID system. The radiation field error was easily observed by edge detection of irradiated field size on EPID image when $0.6^{\circ}$ shift of collimator angle was generated. So, this implemented EPID system could be used as a radiation QA tool.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.38 no.1
• /
• pp.45-52
• /
• 2001

The proximal isovelocity surface area (PISA) method is an effective way of measuring the regurgitant blood flow rate in the mitral valve. This method defines the modelling required to describe the geometry of the isotach of the PISA. In the normal PISA flow model, the flow rate is calculated assuming that the surface of the isotach is either hemispherical or non-hemispherical numerically. However, this paper evaluated the estimate flow rate using a direct surface subdivision flow model based on the height field after isotach extraction using a region-based scheme. To validate the proposed method, the various PISA flow models were compared using pusatile color Doppler images with flow rates ranging from $30\;cm^3/sec\;to\;60\;cm^3/sec$ flow rate. Whereas the hemispherical flow model had a mean value of $29\;cm^3/sec$ and underestimated the measured flow rate by 35%, the proposed model and non-hemispherical model produced a c;ame mean value of $45\;cm^3/sec$, moreover, both flow models produced a similar pulsatile flow rate.

• The Journal of the Korea Contents Association
• /
• v.13 no.1
• /
• pp.1-8
• /
• 2013

The accuracy of a real facial recognition system can be varied according to the accuracy of the eye detection algorithm when we design and implement a semi-automatic facial recognition algorithm depending on the eye position of a database. In this paper, a fully automatic facial recognition algorithm is proposed such that Gabor and LBP features are extracted from fiducial points of a face graph which was created by using fiducial points based on the eyes, nose, mouth and border lines of a face, fitted on the face image. In this algorithm, the recognition performance could be increased because a face graph can be fitted on a face image automatically and fiducial points based LPB features are implemented with the basic Gabor features. The simulation results show that the proposed algorithm can be used in real-time recognition for more than 1,000 faces and produce good recognition performance for each data set.

• Korean Journal of Cognitive Science
• /
• v.7 no.1
• /
• pp.37-56
• /
• 1996

In this paper,we design a verifier for unconstrained handwritten numerals using structural feature analysis,and use it as a comnination algorithm for multiple recognizers.The existing combination algorithms mainly use learnings,statistical methods,or probabilistic methods without considering structural features of numerals.That is why they cannot recognize some numerals which human can identify clearly.To overcome the shortcomings,we design one-to-one verifiers which compare and analyze the relative structural features between frequently confused numeral pairs,and apply them to combine multiple recongnizers.Structural features for verification consist of contour,direction al chain code,polygonal approximation,and zero crossing number of horizontal/vertical projections. We gained a 97.95% reliability with CENPARMI numeral data,and showed that some misconceived factors generated from typical combination algorithms can be removed.

• Journal of Korea Multimedia Society
• /
• v.13 no.10
• /
• pp.1474-1486
• /
• 2010

In this paper, we propose an algorithm which represents the distance depiction technique of real painting that named "Aerial Perspective" in painterly rendering. It is a painting technique that depicts the attenuations of light in the atmosphere, and the scattering effect is changed by the distance, altitude and density of atmospheres. For the reflection of these natures, we use the depth information corresponding to an input image and user-defined parameters, so that user changes the effect level. We calculate the distance and altitude of every pixel with the depth information and parameters about shot information, and control the scattering effects by expression parameters. Additionally, we accentuate the occluding edges detected by the depth information to clarify the sense of distance between fore and back-ground. We apply our algorithm on various landscape scenes, and generate the distance-emphasized results compared to existing works.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.3
• /
• pp.684-689
• /
• 2005

In this paper, we propose car license plate recognition using morphological information and an enhanced neural network. Morphological information on horizontal and vertical edges was used to extract the license plate from a car image. We used a contour tracking algorithm combined with the method of histogram and location information to extract individual characters in the extracted plate. The enhanced neural network is proposed for recognizing them, which has the method of combining the ART-1 and the supervised teaming method. The proposed method has applied to real world car images. The experimental results show that the proposed method has better the extraction rates than the methods with information of the thresholding, the RGB and the HSI, respectively. And the proposed neural network has better recognition performance than the conventional neural networks.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.5
• /
• pp.865-870
• /
• 2006

The cellular neural networks have shown a vast computing power for the image processing in spite of the simplicity of its structure. However, it is impossible to implement the CNN hardware which would require the same enormous amount of cells as that of the pixels involved in the practical large image. In this parer, the $5\times5$ CNN hardware and the pre post processor which can be used for processing the real large image with a time-multiplexing scheme are implemented. The implemented $5\times5$ CNN hardware and pre post processor is applied to the edge detection of $256\times256$ lena image to evaluate the performance. The total number of block. By the time-multiplexing process is about 4,000 blocks and to control pulses are needed to perform the pipelined operation or the each block. By the experimental resorts, the implemented $5\times5$ CNN hardware and pre post processor can be used to the real large image processing.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.1
• /
• pp.80-87
• /
• 2004

In this paper we proposed the novel feature extraction method that is able to extract the individual characters from the license plate area of the car image more precisely by using the RGB color information and the fuzzy binarization newly proposed. The proposed method, first, extracts from the original image the areas that the pixels with the colors around the green are concentrated on as the candidate areas of the license plate, and selects the area with the most intensive distribution of pixels with the white color among the candidate areas as the license plate area. Second the noises of the license plate area should be removed by using 34{\times}$3 Sobel masking, and the fuzzy binarization method are proposed and applied to the license plate area to generate the binarized image of the license plate area. Lastly, the application of the contour tracking algorithm to the binarized area extracts the individual characters from the license plate area. The experiment on a variety of the real car images showed that the proposed method generates the higher rate of success for character extraction than the previous methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.5
• /
• pp.983-989
• /
• 2006

Current emigration and immigration control inspects passports by the naked eye, registers them by manual input, and compares them with items of database. In this paper, we propose the method to recognize information codes of passports. The proposed passport recognition method extracts character-rows of information codes by applying sobel operator, horizontal smearing, and contour tracking algorithm. The extracted letter-row regions is binarized. After a CDM mask is applied to them in order to recover the individual codes, the individual codes are extracted by applying vertical smearing. The recognizing of individual codes is performed by the RBF network whose hidden layer is applied by ART 2 algorithm and whose learning between the hidden layer and the output layer is applied by a generalized delta learning method. After a photo region is extracted from the reference of the starting point of the extracted character-rows of information codes, that region is verified by the information of luminance, edge, and hue. The verified photo region is certified by the classified features by the ART 2 algorithm. The comparing experiment with real passport images confirmed the good performance of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.431-435
• /
• 2008

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판과 구 차량 번호판이 혼합되어 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 형태학적 특징 및 차 연산과 ART2 알고리즘을 이용한 차량 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 차량 번호판 영상에서 차 연산을 이용하여 에지를 추출한 후에 블록 이진화를 한다. 이진화 된 차량 영상에서 신 구 차량 번호판의 형태학적 특성을 8방향 윤곽선 추적 알고리즘에 적용하여 잡음 영역을 제거하고, 차량의 번호판 영역을 추출한다 추출된 번호판 영역에 대하여 평균 이진화와 최대 최소 이진화를 적용하여 번호판의 개별 영역에 대한 형태학적 특성을 고려하여 잡음을 제거하고, Labeling 알고리즘을 적용하여 개별 문자를 추출한 후에 결합한다. 이렇게 분류된 개별 문자 및 숫자 코드를 ART2 알고리즘에 적용하여 학습 및 인식을 한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 녹색 번호판과 흰색 번호판 이미지 각각 100장을 대상으로 실험한 결과, 제시 된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.