• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.65-70
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• 2013

Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.547-559
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• 2010

Delaunay triangulation is suitable for fingerprint matching because of its robustness to rotation and translation. However, missing and spurious minutiae degrade the performance and computational efficiency. In this paper, we propose a method of combining local quality assessment and 4-category minutiae classification to improve accuracy and decrease computational complexity in matching process. Experimental results suggest that removing low quality areas from matching candidate areas and classifying minutiae improve computational efficiency without degrading performance. The results proved that the proposed algorithm outperforms the matching algorithm (BOZORTH3) provided by NIST.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.63-69
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• 2013

A feature-based image recognition method, using features of an object, can be performed faster than a template matching technique. Invariant feature-based panoramic image generation, an application of image recognition, requires large amount of time to match features between two images. This paper proposes a speed-up method of feature matching using feature strength information. Our algorithm extracts features in images, computes their feature strength information, and selects strong features points which are used to match the selected features. The strong features can be referred to as meaningful ones than the weak features. In the experiments, it was shown that our method speeded up over 40% of processing time than the technique without using feature strength information.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.521-523
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• 1999

본 논문에서는 입력 영상 열에서 얼굴 영역을 추출하고, 영역 내 특징점들의 움직임 벡터를 원근 움직임 모델에 정합하여 얼굴 영역을 추적하는 새로운 방법을 제안한다. 제안된 방법은 계층적 형판정합을 이용하여 얼굴 영역을 추출하고, 해당 영역에서 DoG 반응의 국부최대치를 찾아 특징점을 구한다. 그리고 최소제곱추정기법을 이용하여 각 특징점에서 얻어진 움직임 벡터를 원근 모델에 정합한다. 제안된 방법은 선별된 특징점에서 움직임 벡터를 계산함으로써 연산량을 줄일 수 있었고, 원근 움직임 모델을 이용함으로써 잡영에 강한 특성을 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.446-448
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• 1998

본 논문은 두 장의 스테레오 영상으로부터 자동적으로 특징점 정합을 수행하도록 하는 한 방법을 제안한다. Correlation기반의 특징점 정합을 빠르고 안정적으로 수행하며 이 때에 발생하는 애매성 문제에 대한 해결방법을 제시한다. 또한, LMedS방법을 사용하여 outlier를 효과적으로 제거시키고 에피폴라 기하를 이용하여 정합의 성능을 향상시킨다. 실내, 실외 영상에 대한 다양한 실험결과는 본 논문에서 제안하는 방법이 빠르고 효율적임을 보여준다.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.493-502
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• 2007

An on-line registration technique is presented to register multi-view range images for the 3D reconstruction of real objects. Using a range camera, we first acquire range images and photometric images continuously. In the range images, we divide object and background regions using a predefined threshold value. For the coarse registration of the range images, the centroid of the images are used. After refining the registration of range images using a projection-based technique, we use a modified KLT(Kanade-Lucas-Tomasi) tracker to match photometric features in the object images. Using the modified KLT tracker, we can track image features fast and accurately. If a range image fails to register, we acquire new range images and try to register them continuously until the registration process resumes. After enough range images are registered, they are integrated into a 3D model in offline step. Experimental results and error analysis show that the proposed method can be used to reconstruct 3D model very fast and accurately.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.359-361
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• 2008

This paper presents the fuzzy minutiae-based matching to improve the accuracy of the difference between template and imput fingerprint image. Minutiae-based matching method is the most well-known and widely used method for fingerprint matching. However, fingerprint pressure, dryness of the skin, skin disease, sweat, dirt, grease, and humidity in the air cause the noisy fingerprint images and the distortion is produced by users moving their fingers on the scanner surface. The input image may be rejected from the Fingerprint Recognition System, because the distorted fingerprint image is very different from the original image. Large tolerence boxes and fuzzy discriminant function is required to improve the accuracy.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.275-278
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• 2004

지문 인식 방식은 기존의 영상 처리와는 달리 여러 가지 문제점을 포함하고 있다. 지문에는 기준 좌표축이 존재하지 않으므로 회전되어 채취된 지문에 대한 처리가 어려우며, 신체의 일부로서 유연성을 가지고 있어 채취될 때마다 모양이 달라 보이고, 지문이 손상될 수 있어 저 품질의 지문이 빈번히 발생할 수 있다 본 논문에서는 방향성의 흐름 패턴을 이용한 특이점 추출에 초점이 맞춰져 있으며 추출된 특이점 정보는 현재 구현되어진 특징점 추출 정보와 연계해 정합을 위한 기준점으로 활용한다. 기준점을 축으로 생성되어진 직교좌표는 지문 영상의 회전변위에 대한 영향을 최소화 하여 지문의 정합도를 높여준다.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.815-822
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• 2003

Fingerprint image enhancement and minutiae matching are two key steps in an automatic fingerprint identification system. In this paper, we propose a fingerprint recognition technique by using minutiae linking information. Recognition process have three steps ; preprocessing, minutiae extraction, matching step based on minutiae pairing. After extracting minutiae of a fingerprint from its thinned image for accuracy, we introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection with low cost in comparison stage of two fingerprints. This algorithm is invariable to translation and rotation of fingerprint. The matching algorithm was tested on 500 images from the semiconductor chip style scanner, experimental result revealed the false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.101-108
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• 1998

An efficient approach to recognize occluded objects is to detect a number of essential features on the boundary of the unknown shape. The salient points including corner points, tangential points and inflection points are detected by the relation of neighboring pixels of each pixel on the boundaries. Corner points are usually detected in the curvature function and tangential points and inflection points are detected by median filtering the curvature function to avoid the effect of quantization noise as corner points is not sufficient to represent an object with lines and arcs. Then, these salient points are used as features for object matching. Discrete Hopfield Neural Network is used for object matching. Experimental results show that the matching result using salient points is better than those of using corner points only when an object consists of lines and arcs.