• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.49.4-49
• /
• 2001

Digit recognition based on backpropagation neural networks, as an important application of pattern recognition, was attracted much attention. Although it has the advantages of parallel calculation, high error-tolerance, and learning capability, better recognition effects can only be achieved with some specific fixed format input of the digit image. Therefore, digit image preprocessing ability directly affects the accuracy of recognition. Here using Matlab software, the digit image was enhanced by resizing and neutral-rotating the extracted digit image, which improved the digit recognition capability of the backpropagation neural network under practical conditions. This method may also be helpful for recognition of other patterns with backpropagation neural networks.

• 만화애니메이션 연구
• /
• 통권41호
• /
• pp.337-356
• /
• 2015

최근 증강현실 콘텐츠는 광고나 전시 등에서 많이 사용되고 있으며, 어린이들의 동화책으로도 출판되어 판매될 만큼, 대중화되었다. 증강현실 콘텐츠는 현실과 가상을 혼합하여 새로운 예술 공간을 창조하여, 경험자의 몰입도를 높이기 때문에 전시와 광고용 콘텐츠에서 어린이 체험, 교육용 콘텐츠로 다양하게 제작되고 있다. 제작 방법이 복잡하지 않기 때문에, 대학생 과정에서도 간단한 콘텐츠를 개발할 수 있어, 무한한 개발 가능성을 짐작할 수 있다. 증강현실은 카메라로 등록해 놓은 마커를 인식하게 하여 컴퓨터 그래픽 콘텐츠를 그 카메라에 비췬 현실세계에 불러온다. 이때, 증강현실의 제작과정에서는 이미지 인식 기법을 사용하는데, 이는 매우 일반적이며 쉬운 방법이다. 자신이 만든 이미지를 사용할 수도 있기 때문에, 동화책이나 광고에 전반적으로 사용되고 있다. 제작자들이 가장 많이 사용하는 증강현실 마커등록 플랫폼은 퀄컴에서 제공하는 Vuforia이다. 남서울 대학교 가상증강현실 연계전공 학부생들이 제작하여 세종문화회관에 전시된 세 개의 AR콘텐츠는 이미지 인식기법을 사용하였다. 본 연구는 퀄컴에서 제공하는 마커 등록 방법을 학생들이 증강현실 콘텐츠 제작과정에서 사용하면서 시작되었다. 세 개의 각각 다른 이미지를 제작하면서, 마커로 사용하기 위해 Vuforia에서 제공하는 Image Target Manager에 이미지를 등록시키고, 인식률을 조사하여, 인식률을 조금 더 높이기 위해 다양한 방법으로 이미지 제작법을 변경해보았다. 인식률이 높다는 것은 증강현실 콘텐츠를 안정적으로 사용할 수 있음을 의미하기 때문에, 높은 인식률을 가지기 위해, 다양한 시도들을 적용해보았다. 기획의도에 적합한 이미지를 제작하고, 보다 높은 인식률을 위해 몇 가지 방법을 적용하여, 인식률을 비교하였다. 색의 대비, 패턴 등의 요소를 통해 비교하였으며, 그 결과 효율적인 이미지 제작 방안을 제시하였다. 본 연구는 증강현실 콘텐츠의 안정적인 콘텐츠 제작 사례를 제시하고자 한다. 연구의 목적은 이미지 인식 기법을 기반으로 하는 증강현실 콘텐츠의 활용방안과 인식기법의 효과성을 제시하여 증강현실 콘텐츠 개발자들에게 실질적인 도움을 주는 것에 있다.

• Journal of the Optical Society of Korea
• /
• 제15권2호
• /
• pp.140-145
• /
• 2011

Joint transform correlator (JTC) is a well known tool for color pattern recognition for a color image. Color images have red, green and blue components, thus in conventional JTC, three input channels of these color components are necessary for color pattern recognition. This paper proposes a new technique of color pattern recognition by decomposing the color image into three color components and recombining those components into a single gray image in the input plane. This new technique needs single input channel and single output CCD camera, thus a simple JTC can be used. We present various kinds of simulated results to show that our newly proposed technique can accurately recognize and discriminate color differences.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2012년도 추계학술대회
• /
• pp.887-890
• /
• 2012

Image recognition is one of the most important research directions of pattern recognition. Image based road automatic identification technology is widely used in current society, the intelligence has become the trend of the times. This paper studied the image segmentation algorithm theory and its application in road signs recognition system. With the help of image processing technique, respectively, on road signs automatic recognition algorithm of three main parts, namely, image segmentation, character segmentation, image and character recognition, made a systematic study and algorithm. The experimental results show that: the image segmentation algorithm to establish road signs recognition model, can make effective use of smart phone system and application.

• Transactions on Control, Automation and Systems Engineering
• /
• 제2권1호
• /
• pp.76-83
• /
• 2000

A measurement technique of a sea height of burst is introduced for a proximate test using the image recognition of video cameras. In the burst of fuse on the ocean, the burst center of fuse, the sea surface level and the height of calibration poles are measured by the process of image obtained from cameras. Finally, the height of burst of fuse can be computed by Hough transform algorithm. The error compensation algorithms are proposed to eliminate the errors caused by camera level and environmental parameters. As a result of experiment, it has been proved that the proposed measurement system shows the recognition of the center point of the burst image with ${\pm}$0.5m error.

• Journal of Biosystems Engineering
• /
• 제27권2호
• /
• pp.151-160
• /
• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• 한국정보통신학회논문지
• /
• 제25권6호
• /
• pp.774-784
• /
• 2021

객체 검출 및 인식 과정은 컴퓨터비전 분야에서 매우 중요한 과업으로써, 관련 연구가 활발하게 진행되고 있다. 그러나 실제 객체 인식 과정에서는 학습된 이미지 데이터와 테스트 이미지 데이터간 해상도 차이로 인하여 인식기의 정확도 성능이 저하되는 문제가 종종 발생한다. 이를 해결하기 위해 본 논문에서는 객체 인식 정확도 향상을 위한 이미지 초해상도 기법을 제안하여 객체 인식 및 초해상도 통합 프레임워크를 설계하고 개발하였다. 세부적으로는 11,231장의 차량 번호판 훈련용 이미지를 웹 크롤링, 인조데이터 생성 등을 통해 자체적으로 구축하고, 이를 활용하여 이미지 좌우 반전에 강인하도록 목적함수를 정의하여 이미지 초해상도 인공 신경망을 훈련시켰다. 제안 방법의 성능을 검증하기 위해 훈련된 이미지 초해상도 및 번호 인식기 1,999장의 테스트 이미지에 실험하였고, 이를 통해 제안한 초해상도 기법이 문자 인식 정확도 개선 효과가 있음을 확인하였다.

• 통합자연과학논문집
• /
• 제1권2호
• /
• pp.133-139
• /
• 2008

Face recognition technologies using PCA(principal component analysis) recognize faces by deciding representative features of faces in the model image, extracting feature vectors from faces in a image and measuring the distance between them and face representation. Given frequent recognition problems associated with the use of point-to-point distance approach, this study adopted the K-nearest neighbor technique(class-to-class) in which a group of face models of the same class is used as recognition unit for the images inputted on a continual input image. This paper proposes a new PCA recognition in which database of faces.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제4권2호
• /
• pp.117-137
• /
• 2010

Iris recognition is a biometric technique which uses unique iris patterns between the pupil and sclera. The advantage of iris recognition lies in high recognition accuracy; however, for good performance, it requires the diameter of the iris to be greater than 200 pixels in an input image. So, a conventional iris system uses a camera with a costly and bulky zoom lens. To overcome this problem, we propose a new method to restore a low resolution iris image into a high resolution image using a single image. This study has three novelties compared to previous works: (i) To obtain a high resolution iris image, we only use a single iris image. This can solve the problems of conventional restoration methods with multiple images, which need considerable processing time for image capturing and registration. (ii) By using bilinear interpolation and a constrained least squares (CLS) filter based on the degradation model, we obtain a high resolution iris image with high recognition performance at fast speed. (iii) We select the optimized parameters of the CLS filter and degradation model according to the zoom factor of the image in terms of recognition accuracy. Experimental results showed that the accuracy of iris recognition was enhanced using the proposed method.

• Journal of applied mathematics & informatics
• /
• 제15권1_2호
• /
• pp.425-434
• /
• 2004

Pattern recognition in three dimensional image is highly sensitive to assigned value and formation of voxels (pixels for two dimension case). However, occurred while digital imaging, digitization error leads to unpredictable noises in image data. Skeletonization, a powerful tool of pattern recognition, is sensitively dependent on boundary formation. Without successful controlling of the noises, the results of skeletonization can not be allowed as a stable solution. To minimize the effect of noises affecting to boundary formation, we developed a robust processing method useful in skeletonization technique for pattern recognition. Finally, we provide rigorous test results achieved throughout simulation on analytic three dimensional image.