• 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 Broadcast Engineering
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• v.20 no.5
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• pp.728-737
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• 2015

Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.300-304
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• 2020

본 논문에서는 원격 탐사 영상 정합에서 정확도는 유지하면서 특징점 매칭 (Matching) 복잡도를 줄이기 위해 입력 영상을 전처리하는 구조물 검출 네트워크를 이용한 원격 탐사 영상 정합 방법을 제안한다. 영상 정합의 기존 방법은 입력 영상에서 특징점을 추출하고 설명자 (Descriptor)를 생성한다. 본 논문에서 제안하는 방법은 입력 영상에서 특징점 매칭에 영향을 미치는 구조물만 추출하여 새로운 영상을 만들어 특징점을 추출한다. 추출된 특징점은 필터링 (Filtering)을 거쳐 원본 영상에 매핑 (Mapping)되어 설명자를 생성하여 특징점 매칭 속도를 향상시킨다. 또한 구조물 검출 네트워크에서 학습 영상과 시험 영상의 특성의 차이로 생기는 성능 저하 문제를 개선하기 위해 히스토그램 매핑 기법을 이용한다. 아리랑 3 호가 획득한 원격 탐사 영상에 대한 실험을 통해 제안하는 방법은 정확도를 유지하면서 계산 시간을 SURF 보다 87.5%, SIFT 보다 92.6% 감소시킬 수 있다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.39-46
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• 2013

Recently, the mobile industries grow up rapidly and their performances are improved. So the usage of mobile devices is increasing in our life. Also mobile devices equipped with a high-performance camera, so the image stitching can carry out on the mobile devices instead of the desktop. However the mobile devices have limited hardware to perform the image stitching which has a lot of computational complexity. In this paper, we have proposed improved feature descriptor extraction and matching method for efficient image stitching on mobile environment. Our method can reduce computational complexity using extension of orientation window and reduction of dimension feature descriptor when feature descriptor is generated. In addition, the computational complexity of image stitching is reduced through the classification of matching points. In our results, our method makes to improve the computational time of image stitching than the previous method. Therefore our method is suitable for the mobile environment and also that method can make natural-looking stitched image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.407-414
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• 2015

Interest points are generally located at the pixels where height changes occur. So, interest points can be the significant pixels for DSM generation, and these have the important role to generate accurate and reliable matching results. Manual operation is widely used to extract the interest points and to match stereo satellite images using these for generating height information, but it causes economic and time consuming problems. Thus, a tie point extraction method using Harris-affine technique and SIFT(Scale Invariant Feature Transform) descriptors was suggested to analyze height information of buildings in this study. Interest points on buildings were extracted by Harris-affine technique, and tie points were collected efficiently by SIFT descriptors, which is invariant for scale. Searching window for each interest points was used, and direction of tie points pairs were considered for more efficient tie point extraction method. Tie point pairs estimated by proposed method was used to analyze height information of buildings. The result had RMSE values less than 2m comparing to the height information estimated by manual method.

• Journal of KIISE:Software and Applications
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• v.28 no.5
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• pp.440-447
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• 2001

본 논문은 영상과 연관된 3차원 정보로부터 초기 3차원 변환을 유추, 상관윈도우를 변환시켜 정합에 이용하는 새로운 정합기법을 제안한다. 즉, 초기 스테레오 정합 등을 통한 3차원 정보를 추출하고, 인위적인 초기 특징점의 대응을 통해 3차원 변환을 얻으며, 이를 이용해 상관 윈도우의 3차원 변환을 가능하게 한다. 상관 윈도우의 3차원 변환은 기존의 방법이 가지는 영상 흐름의 2차원적인 제한을 이용한 정합방법에 비해 실제 카메라의 변환 유추에 합당하다. 또한 3차원 변환을 통해 정합 대상 점의 탐색범위를 최소화하고 정합의 결과에 신뢰성을 더한다. 실험에서는 다양한 영상의 정합 결과와 기존 방법과의 상관 계수 비교를 통해 본 논문이 제안하는 정합방법의 우월성을 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.626-628
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• 2012

최근 이미지에서 특징점을 추출하고 이를 활용하는 분야로 이미지 스티칭에 대한 연구가 활발하게 진행되고 있다. 이미지 스티칭에서는 특징점을 추출 및 정합이 중요한 요소이다. 본 논문에서는 특징점 기술자의 차원을 효과적으로 감소시켜 정확하면서도 빠르게 정합점을 찾을 수 있는 효율적인 특징점 기술자 생성을 이용한 빠른 이미지 스티칭 기법을 제안한다. 실험 결과, 이미지 스티칭 속도가 기존의 알고리즘 보다 빠르면서도 향상된 스티칭 이미지를 생성할 수 있었다.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.111-122
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• 2010

In this study, a length adjustment algorithm for cyclic signals in manufacturing process using Time Invariant Feature point Extraction and Matching(TIFEM) is proposed. In order to precisely compensate the length of cyclic signals which have irregular length in the middle of signal as well as in the full length more feature points are needed. The extracted feature must involve information about the pattern of signal and should have invariant properties on time and scale. The proposed TIFEM algorithm extracts features having the intrinsic properties of the signal characteristics at first. By using those extracted features, feature vector is constructed for each time point. Among those extracted features, the only effective features are filtered and are chosen such as basis for the length adjustment. And then the partial length adjustment is performed by matching feature points. To verify the performance of the proposed algorithm, the experiments were performed with the experimental data mimicking the three kinds of signals generated from the actual semiconductor process.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.81-88
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• 2015

Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.93-98
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• 2012

Recently, we can easily create high resolution images with digital cameras for high-performance and make use them at variety fields. Especially, the image stitching method which adjusts couple of images has been researched. Image stitching can be used for military purposes such as satellites and reconnaissance aircraft, and computer vision such as medical image and the map. In this paper, we have proposed fast image stitching based on improved SURF algorithm using meaningful features in the process of images matching after extracting features from scenery image. The features are extracted in each image to find out corresponding points. At this time, the meaningful features can be searched by removing the error, such as noise, in extracted features. And these features are used for corresponding points on image matching. The total processing time of image stitching is improved due to the reduced time in searching out corresponding points. In our results, the processing time of feature matching and image stitching is faster than previous algorithms, and also that method can make natural-looking stitched image.