• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.59-64
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• 2013

Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.403-406
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• 2019

논문에서는 스마트 공장 시스템의 표면 결함 검사 시에 영상의 특징인 SIFT, SURF, HOG 특징들을 이용하여 표면 결함 검출에 활용하는 연구를 다루었습니다. 먼저 SIFT, SURF, HOG 특징에 대하여 소개하고 실험에서 이 특징들이 사용될 수 있음을 결과를 통해 보였습니다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.5 no.4
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• pp.384-394
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• 1993

A simple surf zone model is presented The present model takes a quite different approach by showing that wave action is conserved in the surf zone. This condition together with the conservation of energy enables us to develop a surf zone model that requires fewer empirical coefficients. The model is capable of predicting surf zone properties and is presented in analytical forms for the two-dimensional gradually-sloped bottoms. The analytical results were compared favorably with available laboratory data. This surf zone model provides the surface current pattern of the vertical circulation model. and consequently, significantly contributes to solving the three-dimensional current pattern.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.187-206
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• 2002

The purpose of this study is to review the process for the trade settlement system between all parties involved in the commercial transaction under SURF System. SURF application is the latest value added service from bolero.net and a fully automated documentary settlement system. It extends bolero.net's capability to enable trade transactions by providing a delivery versus payment system. It has been designed as a standard, shared, infrastructure component for handling trade settlement within an electronic environment to keep step with the operation of electronic Bolero bill of Lading. It exploits the services provided by the Bolero Core Messaging Platform - secure, guaranteed transactions based on boleroXML standards to provide document compliance services with optional bank guarantees. So, SURF system can automatically check all commonly used trade documents such as commercial invoices, bills of lading and certificates of weight and analysis, etc and supports a full range of settlement options including Open Account, Documentary Collections, Documentary Credit. 58 have key features as follows, ① automatic document compliance checking, ② integrated with the Title Registry, ③ supports various forms of vender financing, ④ governed by a set of legally binding rules, ⑤ fully prepared for Straight-Through-Processing, ⑥ Enabled compliance with UCP 500.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.53-59
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• 2015

Since the amount of digital image continues to grow in usage, users feel increased difficulty in finding specific images from the image collection. This paper proposes a novel image searching scheme that extracts the image feature using combination of Advanced SURF (Speed-Up Robust Feature) and DCD (Dominant Color Descriptor). The key point of this research is to provide a new feature extraction algorithm to improve the existing SURF method with removal of unnecessary feature in image retrieval, which can be adaptable to mobile system and efficiently run on the mobile environments. To evaluate the proposed scheme, we assessed the performance of simulation in term of average precision and F-score on two databases, commonly used in the field of image retrieval. The experimental results revealed that the proposed algorithm exhibited a significant improvement of over 14.4% in retrieval effectiveness, compared to OpenSURF. The main contribution of this paper is that the proposed approach achieves high accuracy and stability by using ASURF and DCD in searching for natural image on mobile platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5624-5638
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• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5471-5478
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• 2012

In this paper, we propose a new short-circuit detecting method which can detect bad short-circuits, one of bad types occurring in PCB(Printed Circuit Board), by using SURF(Speeded-Up Robust Features) algorithm. The basic procedure in the proposed method sequentially consists of extracting features from both sample and inputted images by SURF, performing perspective transform by feature matching and matching results, extracting check areas of interest, binary coding and extracting short-circuits, and verifying results. The proposed method focuses on the robustness which can detect bad short-circuits even though the position and angle of PCB are not uniform and arbitrarily placed. Experimental results show that our method enables to detect bad short-circuits regardless of the location and angle of PCB placed variously and validate that the proposed method outperforms the conventional methods detecting bad short-circuits manually on the aspect of both the detection rate and time.

• Journal of Ocean Engineering and Technology
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• v.22 no.5
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• pp.52-60
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• 2008

This study investigates the applicability of CADMAS-SURF (Super Roller Flume for Computer Aided Design of a MArtime Structure) code basal on the Navier-Stokes solver to predict bore phenomena. The time variation of ware levels and velocities due to the bore propagation were computed for the different bore strength conditions. In order to verify the numerical results by CADMAS-SURF, laboratory experiments were also performed, using the DPIV and LDV measuring system. The numerical results were compared to the experimental data and the analytical predictions by the NSC method basal on fully nonlinear shallow-water theory by the method of characteristics. It appears that the CADMAS-SURF slightly overestimated the water-surface level measured by the laboratory experiments and its discrepancy becomes prominent as the bore strength increases. The predicted propagation speed for a bore was also slaver than that by the experiment and NSC method. However, the temporal variations in velocities were in relatively good agreement with the experimental data for all cases, except for overshooting and undershooting in the front face of a bore, which may be derived from the numerical instability. Further, CADMAS-SURF successfully simulated the decrease in the water level and velocity caused by the effects of negative waves reflected from the upstream end wall.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.140-146
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• 2011

In this paper, we propose a fast object classification method based on texture and color information for video surveillance. We take the advantage of local patches by extracting SURF and color histogram from images. SURF gives intensity content information and color information strengthens distinctiveness by providing links to patch content. We achieve the advantages of fast computation of SURF as well as color cues of objects. We use Bag of Word models to generate global descriptors of a region of interest (ROI) or an image using the local features, and Na$\ddot{i}$ve Bayes model for classifying the global descriptor. In this paper, we also investigate discriminative descriptor named Scale Invariant Feature Transform (SIFT). Our experiment result for 4 classes of the objects shows 95.75% of classification rate.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.71-80
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• 2012

This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle's location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road.