• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.37 no.3
• /
• pp.104-113
• /
• 2000

In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.4
• /
• pp.381-391
• /
• 2001

This paper presents an efficient approach to build an image mosaics from image sequences. Unlike general panoramic stitching methods, which usually require some geometrical feature points or solve the iterative nonlinear equations, our algorithm can directly recover the 8-parameter planar perspective transforms. We use four quasi-feature points in order to compute the projective transform between two images. This feature is based on the graylevel distribution and defined in the overlap area between two images. Therefore the proposed algorithm can reduce the total amount of the computation. We also present an algorithm lot efficiently matching the correspondence of the extracted feature. The proposed algorithm is applied to various images to estimate its performance and. the simulation results present that our algorithm can find the correct correspondence and build an image mosaics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.986-989
• /
• 2003

In the steel production line, the molten metal of a furnace is transformed into slab material and then move to the hot strip line, This paper describe about the real time recognition system of material management number, which is marked at the surface of a slab in the steel production line. This recognition processing should be performed before the slab is moved to the hot strip line. This system include following recognition steps. First, we remove noise from the captured slab image by use pre-filter. Second, we extract rough area, which is include slab number and then, we extract individual number area. Finally, we recognize material management number by use KLT(Karhunen-Loeve transform) algorithm. We applied our system to the real slave image, which was captured in the process line. In the results, we recognized slave number to the 94% accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.413-417
• /
• 2007

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판 차량이 꾸준히 증가하고 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차 관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 신 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 지능형 신 자동차 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 신 차량 영상을 그레이 레벨로 변환한 후에 블록 이진화한다. 블록 이진화된 차량 영상을 대상으로 차량의 형태학적 특징을 적용하여 잡음을 제거한 후, 번호판 영역을 추출한다. 추출된 번호판 영역에 대해 Grassfire 알고리즘을 적용하여 개별 코드를 추출한다. 차량 번호판을 인식하기 위하여 추출된 개별 코드를 퍼지 ART 알고리즘을 적용하여 학습 및 인식한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 100장의 차량 영상을 대상으로 실험한 결과, 제안된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.6
• /
• pp.669-678
• /
• 2002

Currently, the domestic interests on the development of eyesight related measuring instruments are being increased. So we are developing such an electronic system of Refracto-keratometer, which contains a software and a hardware both. If this system could inform the examiner of the precise eyesight measuring result from the treatment of the image of optical system, then potentially the number of missed measuring results could be reduced. Our electronic system has been developed from the two areas divided into a software and a hardware. The software area was focused on the more exact eyesight measuring results, using morphological filtering methods and gray-leveled signal enhancing techniques. The hardware area is performing the same functions as the existing other systems. Besides, it provides the embedded software with free variables which could reduce the developing duration sharply as well as enlarge many kinds of application-extensions. Therefore, this electronic system has made effective eyesight measurement possible as the result of reducing the differences applied to sophisticated eyesight measurement.

• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.2
• /
• pp.65-72
• /
• 2011

In this paper, a real-time monocular vision based navigation system is developed for the disabled people, where online background learning and vector field histogram are used for identifying obstacles and recognizing avoidable paths. The proposed system is performed by three steps: obstacle classification, occupancy grid map generation and VFH-based path recommendation. Firstly, the obstacles are discriminated from images by subtracting with background model which is learned in real time. Thereafter, based on the classification results, an occupancy map sized at $32{\times}24$ is produced, each cell of which represents its own risk by 10 gray levels. Finally, the polar histogram is drawn from the occupancy map, then the sectors corresponding to the valley are chosen as safe paths. To assess the effectiveness of the proposed system, it was tested with a variety of obstacles at indoors and outdoors, then it showed the a'ccuracy of 88%. Moreover, it showed the superior performance when comparing with sensor based navigation systems, which proved the feasibility of the proposed system in using assistive devices of disabled people.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.273-278
• /
• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• Journal of Digital Contents Society
• /
• v.15 no.6
• /
• pp.675-682
• /
• 2014

Prostate is only an organ of men. To diagnose the disease of the prostate, generally transrectal ultrasound(TRUS) images are used. Detecting its boundary is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Support Vector Machine(SVM) is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing. Gabor filter bank for extraction of rotation-invariant texture features has been implemented. SVM for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted. A number of experiments are conducted to validate this method and results shows that the proposed algorithm extracted the prostate boundary with less than 10% relative to boundary provided manually by doctors.

• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.35T no.3
• /
• pp.120-127
• /
• 1998

In this paper, ultrasonic images of 25MHz bandwidth were acquired by applying peak value variation, time average and depth profile algorithm to acoustic microscopy and its performance was compared and analysed with each other. In the time average algorithm, total reflecting pulse wave from a spot on the coin was converted to digital data in time domain and average value of the converted 512 data was calculated in computer. Time average image was displayed by gray levels colour of acquired N x N matrix average data in the scanning area on the sample. This technique having smoothing effects in time domain make developed an ultrasonic image on a highly scattering area. In depth profile technique, time difference between the reference and the reflected signal was detected with minimum resolution performance of 2ns, thus we can acquired real 3 dimensional shape of the scanning area in accordance with relative magnitude. Through these experiments, peak value, time average and depth profile images were analysed and advantages of each algorithm were proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.267-270
• /
• 2016

Currently, tire has a variety of information to know the information of the tire are displayed on the tire side. the market are marked with raised letters showing a variety of information relating to the tires. Such information enables people and tire related companies to distinguish between tires upon the information marked on the tires. Generally, people see the information including max press, manufacturing date, etc. Accordingly, studies on automated recognition of raised letters on tire by using image processing technology have been presented consistently. However, they lack a method for recognition of letters and improvement of the recognition. Moreover, the raised letters have been previously recognized through image processing. Further, to obtain the character recognition of a conventional side in video, it is suitably utilized the effects of lighting time of acquisition, so as part of the background and the character has a gray level values between approximately the same, is the part that is not relatively clear are many scattered. In this paper, we see the characters of the tire side using the laser sensor, recognition, was designed for character recognition of the tire side.