• Composites Research
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• 제33권5호
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• pp.296-301
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• 2020

적층복합재는 면내 방향의 물성은 우수하지만 두께 방향의 물성이 취약하여 굽힘, 비틀림하중이 가해질 때 층간 분리(Delamination) 현상이 쉽게 나타난다. 층간 분리 현상을 지연하는 복합재의 두께 방향 물성 보강법으로는 Z-pinning, Stitching, Tufting 등이 있으며, 대표적으로 Z-pinning과 Stitching 공법을 많이 사용한다. Z-pinning 공법은 prepreg의 두께 방향으로 금속 핀이나 카본 핀을 적용하여 보강하는 공법이고, Stitching 공법은 프리폼에 상부 및 하부 섬유를 교차시켜 두께방향으로 기계적 강도를 향상시키는 방법이다. 본 논문에서는 Z-pinning과 Stitching 공법의 단점을 보완 및 개선한 I-fiber stitching 공법을 제안하였으며, 본 공법이 적용된 복합재 Single-lap joint의 정적 강도를 평가하였다. Single-lap joint 시편은 오토클레이브 진공백 공정을 사용하여 동시경화법으로 제작하였다. 복합재 시편 두께는 고정하였으며, Stitching 패턴(5×5, 7×7)과 삽입 각도(0°, 45°)를 변화시켜가며 총 5 종류의 시편을 제작하였다. 시험 결과, I-fiber stitching 공법을 적용한 시편의 파손하중은 보강하지 않은 시편의 파손하중 대비 최대 143% 증가하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4527-4548
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• 2017

This paper proposes a method to generate panoramic images by combining conventional feature extraction algorithms (e.g., SIFT, SURF, MPEG-7 CDVS) with sensed data from inertia sensors to enhance the stitching results. The challenge of image stitching increases when the images are taken from two different mobile phones with no posture calibration. Using inertia sensor data obtained by the mobile phone, images with different yaw, pitch, and roll angles are preprocessed and adjusted before performing stitching process. Performance of stitching (e.g., feature extraction time, inlier point numbers, stitching accuracy) between conventional feature extraction algorithms is reported along with the stitching performance with/without using the inertia sensor data. In addition, the stitching accuracy of video data was improved using the same sensed data, with discrete calculation of homograph matrix. The experimental results for stitching accuracies and speed using sensed data are presented in this paper.

• 한국멀티미디어학회논문지
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• 제17권10호
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• pp.1205-1212
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• 2014

In this paper, we propose a high-quality stitching method of 3D multiple dental CT images. First, a weighted function is generated using the difference of two distance functions that calculate a distance from the nearest edge of an overlapped region to each position. And a blending ratio propagation function for two gradient vectors is parameterized by the difference and magnitude of gradient vectors that is also applied by the weighted function. When the blending ratio is propagated, an improved region growing scheme is proposed to decide the next position and calculate the blending intensity. The proposed method produces a high-quality stitching image. Our method removes the seam artifact caused by the mean intensity difference between images and vignetting effect. And it removes double edges caused by local misalignment. Experimental results showed that the proposed method produced high-quality stitching images for ten patients. Our stitching method could be usefully applied into the stitching of 3D or 2D multiple images.

• 한국멀티미디어학회논문지
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• 제18권6호
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• pp.701-709
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• 2015

Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

• Elastomers and Composites
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• 제57권4호
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• pp.157-164
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• 2022

Representative bulletproof materials, such as aramid or ultra-high molecular weight polyethylene(UHMWPE), have excellent strength and modulus in the plane direction but are very vulnerable to forces applied in the thickness direction. This paper reports a study on the effects of reinforcement in the thickness direction when bulletproof composite fabrics are prepared to improve their performance. Aramid and UHMWPE fabrics were combined using the film-bonding, needle-punching, or stitching methods and then subjected to low-velocity projectile and ball-drop impact tests. The results of the low-velocity projectile test indicated that the backface signature(BFS) decreased by up to 29.2% in fabrics obtained via the film-bonding method. However, the weight of the film-bonded fabric increased by approximately 23% compared with that obtained by simple lamination, and the fabric stiffened on account of the binder. Flexibility, light weight for wearability, and excellent bulletproof performance are very important factors in the development of bulletproof materials. When the needle-punching method was used, the BFS increased as the fibers sustained damage by the needle. When the composite fabrics were combined by stitching, no significant difference in weight and thickness was observed, and the BFS showed similar results. When a diagonal stitching pattern was employed, the BFS decreased as the stitching density increased. By contrast, when a diamond stitching pattern was used, the fabric fibers were damaged and the BFS increased as the stitching density increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1648-1672
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• 2020

There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image's inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.705-711
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• 2000

This paper presents a fast 3D mesh generation method using a surface based method with a stitching algorithm. This method uses the surface based method since the volume based method that uses 3D Delaunay triangulation can hardly deal with a large scale of scanned points. To reduce the processing time, this method also uses a stitching algorithm: after dividing the whole point data into several sections and performing mesh generation on individual sections, the meshes from several sections are stitched into one mesh. Stitching method prevents the surface based method from increasing the processing time exponentially as the number of the points increases. This method works well with different types of scanned points: a scattered type points from a conventional 3D scanner and a cross-sectional type from CT or MRI.

• International Journal of CAD/CAM
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• 제9권1호
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• pp.71-77
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• 2010

Various applications, such as mesh composition and model repair, ask for a natural stitching for polygonal surfaces. Unlike the existing algorithms, we make full use of the information from the two feature lines to be stitched up, and present an accurate stitching method for polygonal surfaces, which minimizes the error between the feature lines. Given two directional polylines as the feature lines on polygonal surfaces, we modify the general placement method for points matching and arrive at a closed-form solution for optimal rotation and translation between the polylines. Following calculating out the stitching line, a local surface optimization method is designed and employed for postprocess in order to gain a natural blending of the stitching region.

• 한국컴퓨터정보학회논문지
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• 제18권10호
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• pp.39-46
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• 2013

최근 모바일 산업이 발달하고 성능이 향상되어 생활 속에서 모바일 기기의 사용량이 늘고 있다. 현재 모바일 기기에는 고성능 카메라를 장착하고 있어 데스크톱에서 수행하던 영상 정합을 모바일 기기에서 수행할 수 있다. 그러나 모바일 기기는 제한된 하드웨어 자원을 가지고 있어 영상 정합을 수행하기에 연산량이 많다. 따라서 본 논문에서는 모바일 환경에서 효율적인 영상 정합을 위한 향상된 특징점 기술자 추출 및 정합 기법 제안한다. 특징점 기술자 생성시 방향 윈도우 확장 및 기술자의 차원을 줄여 정확도를 높이면서 연산량을 감소시킨다. 또한 정합점 분류 기법을 통하여 영상 정합의 연산량을 감소시킨다. 실험결과 기존의 방법보다 영상 정합 속도가 향상되어 모바일 환경에 적합하면서도 자연스러운 영상을 생성할 수 있었다.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.341-344
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• 2014

This study proposes a modified sub-aperture stitching algorithm, which uses an image sharpening algorithm and particle swarm optimization to improve the stitching accuracy. In sub-aperture stitching interferometers with high positional accuracy, the high-frequency components of measurements are more important than the low-frequency components when compensating for position errors using a sub-aperture stitching algorithm. Thus we use image sharpening algorithms to strengthen the high-frequency components of measurements. When using image sharpening algorithms, sub-aperture stitching algorithms based on the least-squares method easily become trapped at locally optimal solutions. However, particle swarm optimization is less likely to become trapped at a locally optimal solution, thus we utilized this method to develop a more robust algorithm. The results of simulations showed that our algorithm compensated for position errors more effectively than the existing algorithm. An experimental comparison with full aperture-testing results demonstrated the validity of the new algorithm.