Efficient Unsupervised Image Stitching Using Attention Mechanism with Deep Homography Estimation

Traditional feature-based image stitching techniques often encounter obstacles when dealing with images lackingunique attributes or suffering from quality degradation. The scarcity of annotated datasets in real-life scenesseverely undermines the reliability of supervised learning methods in image stitching. Furthermore, existing deeplearning architectures designed for image stitching are often too bulky to be deployed on mobile and peripheralcomputing devices. To address these challenges, this study proposes a novel unsupervised image stitching methodbased on the YOLOv8 (You Only Look Once version 8) framework that introduces deep homography networksand attentionmechanisms. Themethodology is partitioned into three distinct stages. The initial stage combines theattention mechanism with a pooling pyramid model to enhance the detection and recognition of compact objectsin images, the task of the deep homography networks module is to estimate the global homography of the inputimages consideringmultiple viewpoints. The second stage involves preliminary stitching of the masks generated inthe initial stage and further enhancement through weighted computation to eliminate common stitching artifacts.The final stage is characterized by adaptive reconstruction and careful refinement of the initial stitching results.Comprehensive experiments acrossmultiple datasets are executed tometiculously assess the proposed model. Ourmethod’s Peak Signal-to-Noise Ratio (PSNR) and Structure Similarity Index Measure (SSIM) improved by 10.6%and 6%. These experimental results confirm the efficacy and utility of the presented model in this paper.

Research on Stitching Algorithm Based on Tree Branch Image

Branch identification technology is a key technology to achieve automated pruning of fruit tree branches, and one of its technical bottlenecks lies in the stitching of branch images. To this end, we propose a set of branch image stitching technology algorithms. The algorithm is based on the grey-scale prime centroid method to determine the detection feature points, and uses the coordinate transformation matrix H of the corresponding points of the image to carry out the image geometric transformation, and realises the feature matching through sample comparison and classification methods. The experimental results show that the matched point images are more correct and less time-consuming.

A Gridless Router Based on Hierarchical PB Corner Stitching Structure

A multi layer gridless area router is reported.Based on corner stitching,this router adopts tile expansion to explore path for each net.A heuristic method that penalizes nodes deviating from the destination is devised to accelerate the algorithm.Besides,an enhanced interval tree is used to manage the intermediate data structure.In order to improve the completion rate of routing,a new gridless rip up and rerouting algorithm is proposed.The experimental results indicate that the completion rate is improved after the rip up and reroute process and the speed of this algorithm is satisfactory.

Computer aided stitching approach for dental restoration models

According to the bio-characteristics of the lower and upper cavity surfaces of dental restoration, a stitching approach is proposed based on a virtual zipper working mechanism and a minimization of the surface total curvature energy, which is used to resolve the stitching problems existing during computer-aided design for dental restorations. First, the two boundaries corresponding to the lower and upper surfaces are triangulated based on the zipper working mechanism to generate the initial stitching surface patch, of which the edges are distributed uniformly between the boundaries. Secondly, the initial stitching surface patch is subdivided and deformed to reconstruct an optimized surface patch according to the bio-characteristics of the teeth. The optimized surface patch is minimally distinguishable from the surrounding mesh in smoothness and density, and it can stitch the upper and lower cavity surfaces naturally. The experimental results show that the dental restorations obtained by the proposed method can satisfy both the shape aesthetic and the fitting accuracy, and meet the requirements of clinical oral medicine.

Recent Situation of Acupuncture and Moxibustion in the Treatment of Stomach Pain with Deficiency and Cold of Spleen and Stomach

Stomachache is one of the most common diseases of digestive system, among which stomach pain of deficiency cold of spleen and stomach is the most common. Acupuncture and moxibustion therapy as an external treatment of traditional Chinese medicine for relieving stomach pain due to deficiency of spleen and stomach, has the advantages of convenient operation, small adverse reactions and remarkable curative effect, which is easy for patients to accept. In this paper, acupuncture and moxibustion therapy such as moxibustion and warm acupuncture therapy for stomach pain of spleen and stomach deficiency cold type is summarized to provide evidence-based basis for clinical treatment of stomach pain of spleen and stomach deficiency cold type.

Tensile Mechanical Behavior and Failure Mechanism of a Plain-Woven SiCf/SiC Composites at Room and Elevated Temperatures

Ceramic matrix composites (CMCs) are the preferred materials for solving advanced aerospace high-temperature structural components;it has the comprehensive advantages of higher temperature (~1500˚C) and low density. In service environments, CMCs exhibit complex damage mechanisms and failure modes, which are affected by constituent materials, meso-architecture and inhere defects. In this paper, the in-plane tensile mechanical behavior of a plain-woven SiCf/SiC composite at room and elevated temperatures was investigated, and the factors affecting the tensile strength of the material were discussed in depth. The results show that the tensile modulus and strength of SiCf/SiC composites at high temperature are lower, but the fracture strain increases and the toughness of the composites is enhanced;the stitching holes significantly weaken the tensile strength of the material, resulting in the material is easy to break at the cross-section with stitching holes.

Predicting the Stitch Density of Finished Fabrics Using Weft Blended Grey Knit Fabrics

Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, yarn diameter and linear density, and fabric structure. Selecting stitch density (wales per inch, course per inch) is essential to getting the appropriate fabric weight and desired quality. Usually, no rules or assumptions exist to get the desired stitch density in the finished fabric stage. Fifteen types of blended knit fabrics were prepared to conduct the study. The varying percentages of cotton, polyester, and elastane are incorporated in the blends. Regression analysis and regression ANOVA tests were done to predict the stitch density of finished fabrics. A suitable regression equation is established to get the desired results. The study also found that the stitch density value in the finished stage fabric decreases by approximately 15% compared to the stitch density in the grey fabric stage. This study will help the fabric manufacturers get the finished fabric stitch density in advance by utilizing the grey fabric stitch density data set. The author expects this research to benefit the knitting and dyeing industry, new researchers, and advanced researchers.

A morphology-stitching method to improve Landsat SLC-off images with stripes

Stripes are artifacts in satellite images caused by various factors such as hardware defects. In some cases, these artifacts are introduced by some mitigating algorithms like Landsat SLC-off （Scan Line Corrector） gap-filling methods of LLHM （Local Linear Histogram Matching） and AWLHM （Adaptive Window Linear Histogram Matching）, which leave stripes as a byproduct. To improve Landsat SLC-off images with stripes,we propose an algorithm involving some hypothetical stripe-crossing stitch lines using the mean pixel value of the stitch lines.

Underwater Terrain Image Stitching Based on Spatial Gradient Feature Block

At present,underwater terrain images are all strip-shaped small fragment images preprocessed by the side-scan sonar imaging system.However,the processed underwater terrain images have inconspicuous and few feature points.In order to better realize the stitching of underwater terrain images and solve the problems of slow traditional image stitching speed,we proposed an improved algorithm for underwater terrain image stitching based on spatial gradient feature block.First,the spatial gradient fuzzy C-Means algorithm is used to divide the underwater terrain image into feature blocks with the fusion of spatial gradient information.The accelerated-KAZE(AKAZE)algorithm is used to combine the feature block information to match the reference image and the target image.Then,the random sample consensus(RANSAC)is applied to optimize the matching results.Finally,image fusion is performed with the global homography and the optimal seam-line method to improve the accuracy of image overlay fusion.The experimental results show that the proposed method in this paper effectively divides images into feature blocks by combining spatial information and gradient information,which not only solves the problem of stitching failure of underwater terrain images due to unobvious features,and further reduces the sensitivity to noise,but also effectively reduces the iterative calculation in the feature point matching process of the traditional method,and improves the stitching speed.Ghosting and shape warping are significantly eliminated by re-optimizing the overlap of the image.

A survey on image and video stitching

Image/video stitching is a technology for solving the field of view(FOV)limitation of images/videos.It stitches multiple overlapping images/videos to generate a wide-FOV image/video,and has been used in various fields such as sports broadcasting,video surveillance,street view,and entertainment.This survey reviews image/video stitching algorithms,with a particular focus on those developed in recent years.Image stitching first calculates the corresponding relationships between multiple overlapping images,deforms and aligns the matched images,and then blends the aligned images to generate a wide-FOV image.A seamless method is always adopted to eliminate such potential flaws as ghosting and blurring caused by parallax or objects moving across the overlapping regions.Video stitching is the further extension of image stitching.It usually stitches selected frames of original videos to generate a stitching template by performing image stitching algorithms,and the subsequent frames can then be stitched according to the template.Video stitching is more complicated with moving objects or violent camera movement,because these factors introduce jitter,shakiness,ghosting,and blurring.Foreground detection technique is usually combined into stitching to eliminate ghosting and blurring,while video stabilization algorithms are adopted to solve the jitter and shakiness.This paper further discusses panoramic stitching as a special-extension of image/video stitching.Panoramic stitching is currently the most widely used application in stitching.This survey reviews the latest image/video stitching methods,and introduces the fundamental principles/advantages/weaknesses of image/video stitching algorithms.Image/video stitching faces long-term challenges such as wide baseline,large parallax,and low-texture problem in the overlapping region.New technologies may present new opportunities to address these issues,such as deep learning-based semantic correspondence,and 3D image stitching.Finally,this survey discusses the challenges of image/video stitching and proposes potential solutions.

Efficient Image Stitching in the Presence of Dynamic Objects and Structure Misalignment

This paper presents a new method for simultaneously eliminating visual artifacts caused by moving objects and structure misalignment in image stitching. Given that the input images are roughly aligned, our approach is implemented in two stages. In the first stage, we discover motions between input images, and then extract their corresponding regions through a multi-seed based region growing algorithm. In the second stage, with prior information provided by the extracted regions, we perform a graph cut optimization in gradient-domain to determine which pixels to use from each image to achieve seamless stitching. Our method is simple to implement and effective. The experimental results illustrate that the proposed approach can produce comparable or superior results in comparison with state-of-the-art methods.

DYNAMICS OF THE LOOPER DRIVE MECHANISM ON A BLIND STITCHING MACHINE

The looper drive mechanism is a main moving part in the blind stitching machine, which is aspatial 5 bar RRRSR linkage. In this paper, a dynamic analysis of the looper drive mechanism is made by means of the ma-trix method. Two methods are adopted in the calculation of the shaking force and shaking moment, one isdone by the constraint reaction of the flame-connected kinematic parts; the other is the inertialforces of all moving links.

Fabricating a smart clothing system based on strain-sensing yarn and novel stitching technology for health monitoring

Various yarn-shaped flexible strain sensors have recently been developed.However,research is lacking on additive manufacturing for smart clothing for integrating yarn sensors with commercial garments.Herein,a strain-sensing yarn is sewn into a piece of fabric through a novel stitching technique,and the influence of the stitching method and needle pitch on the sensing performance is investigated using finite element analysis(FEA).The sensing performance could be improved when the sensing yarn is self-locked in the fabric at the needle eyes,and the needle pitch was reduced to 0.5 cm,which is attributed to the enhanced stress and strain concentration.Meanwhile,the composite sensing fabric featured outstanding performance,including a low detection limit(0.1%),rapid response(280 ms),excellent durability(10000 cycles),and high stability(negligible drift and frequency independence).In addition,the remarkable wear resistance,washability,and anti-interference to ambient humidity and perspiration were obtained.Therein,the optimal stitch trace lengths of sensing yarn for detecting elbow motion,breathing,and heartbeats are discussed.Finally,a smart clothing system composed of smart clothing,data acquisition unit,and mobile APP was developed to simultaneously detect human movement and physiological signals.This work provides a reference to produce intelligent garments based on yarn sensors for health monitoring.

Unsupervised Oral Endoscope Image Stitching Algorithm

Oral endoscope image stitching algorithm is studied to obtain wide-field oral images through regis-tration and stitching,which is of great significance for auxiliary diagnosis.Compared with natural images,oral images have lower textures and fewer features.However,traditional feature-based image stitching methods rely heavily on feature extraction quality,often showing an unsatisfactory performance when stitching images with few features.Moreover,due to the hand-held shooting,there are large depth and perspective disparities between the captured images,which also pose a challenge to image stitching.To overcome the above problems,we propose an unsupervised oral endoscope image stitching algorithm based on the extraction of overlapping regions and the loss of deep features.In the registration stage,we extract the overlapping region of the input images by sketching polygon intersection for feature points screening and estimate homography from coarse to fine on a three-layer feature pyramid structure.Moreover,we calculate loss using deep features instead of pixel values to emphasize the importance of depth disparities in homography estimation.Finally,we reconstruct the stitched images from feature to pixel,which can eliminate artifacts caused by large parallax.Our method is compared with both feature-based and previous deep-based methods on the UDIS-D dataset and our oral endoscopy image dataset.The experimental results show that our algorithm can achieve higher homography estimation accuracy,and better visual quality,and can be effectively applied to oral endoscope image stitching.

Stitch welding of Ti-6Al-4V titanium alloy by fiber laser

Stitch welding of plate covered skeleton structure of Ti-6Al-4V titanium alloys has a variety of applications in aerospace vehicle manufacture. The laser stitch welding of Ti-6Al-4V titanium alloys was carried out by a 4 kW ROFIN fiber laser. Influences of laser welding parameters on the macroscopic geometry, porosity, microstructure and mechanical properties of the stitch welded seams were investigated by digital microscope, optical microscope, scanning electron microscope and universal tensile testing machine. The results showed that the three-pipe nozzle with gas flow rate larger than 5 L/min could avoid oxidization, presenting better shielding effect in comparison with the single-pipe nozzle. Porosity formation could be suppressed with the gap between plate and skeleton less than 0.1 mm, while the existing porosity can be reduced with remelting. The maximum shear strength of stitch welding joint with minimal porosity was obtained by employing laser power of 1700 W, welding speed of 1.5 m/min and defocusing distance of ＋8 ram.

An All-E-Beam Lithography Process for the Patterning of 2D Photonic Crystal Waveguide Devices

We present an all-e-beam lithography （EBL） process for the patterning of photonic crystal waveguides. The whole device structures are exposed in two steps. Holes constituting the photonic crystal lattice and defects are first exposed with a small exposure step size （less than 10nm）. With the introduction of the additional proximity effect to compensate the original proximity effect, the shape, size, and position of the holes can be well controlled. The second step is the exposure of the access waveguides at a larger step size （about 30nm） to improve the scan speed of the EBL. The influence of write-field stitching error can be alleviated by replacing the original waveguides with tapered waveguides at the joint of adjacent write-fields. It is found experimentally that a higher exposure efficiency is achieved with a larger step size;however,a larger step size requires a higher dose.

Stitch Fix 数据驱动的服装零售公司

Stitch Fix运用大数据技术改造甚至颠覆了传统的服装零售业,其数据驱动的新零售模式,对我国正在推动的大数据战略下的商业模式创新具有借鉴意义。2011年成立于美国旧金山的Stitch Fix是一家服装零售公司,同时也是一家大数据科技公司。除了提供自有服饰品牌外,Stitch Fix还提供700多个流行服装品牌,其商业模式充分展现了线上线下结合并以数据为驱动力的新零售业态。

Underwater Image Bidirectional Matching for Localization Based on SIFT

For the purpose of identifying the stern of the SWATH （Small Waterplane Area Twin Hull） availably and perfecting the detection technique of the SWATH ship＇s performance, this paper presents a novel bidirectional image registration strategy and mosaicing technique based on the scale invariant feature transform （SIFT） algorithm. The proposed method can help us observe the stern with a great visual angle for analyzing the performance of the control fins of the SWATH. SIFT is one of the most effective local features of the scale, rotation and illumination invariant. However, there are a few false match rates in this algorithm. In terms of underwater machine vision, only by acquiring an accurate match rate can we find an underwater robot rapidly and identify the location of the object. Therefore, firstly, the selection of the match ratio principle is put forward in this paper; secondly, some advantages of the bidirectional registration algorithm are concluded by analyzing the characteristics of the unidirectional matching method. Finally, an automatic underwater image splicing method is proposed on the basis of fixed dimension, and then the edge of the image＇s overlapping section is merged by the principal components analysis algorithm. The experimental results achieve a better registration and smooth mosaicing effect, demonstrating that the proposed method is effective.

A PREDICTIVE APPROACH TO THE IN-PLANE MECHANICAL PROPERTIES OF STITCHED COMPOSITE LAMINATES

This contribution attempts to model the alteration of the in-plane elastic properties in laminates caused by stitching, and to predict the in-plane effective tensile strength of the stitched composite laminates. The distortion of in-plane fibers is considered to be the main cause that affects the in-plane mechanical properties. A fiber distortion model is proposed to characterize the fiber misalignment and the fiber content concentration due to stitching. The undistorted region, the fiber distortion region, the resin-rich pocket and the through-thickness reinforcement section are taken into account. The fiber misalignment and inhomogeneous fiber content due to stitching have been formulated by introducing two parameters, the distortion width and maximum misalignment. It has been found that the ply stress concentration in stitched laminates is influenced by the two concurrent factors, the stitch hole and inhomogeneous fiber content. The stitch hole brings about the stress concentration whereas the higher fiber content at the local region induced by stitching restrains the local deformation of the composite. The model is used to predict the tensile strength of the [0/45/0/-45/90/45/0/-45]58 T300/QY9512 composite laminate stitched by Kevlar 29 yarn with different stitching configurations, showing an acceptable agreement with experimental data.

Multi-camera calibration method based on minimizing the difference of reprojection error vectors

In order to achieve a high precision in three-dimensional（3D） multi-camera measurement system, an efficient multi-cameracalibration method is proposed. A stitching method of large scalecalibration targets is deduced, and a fundamental of multi-cameracalibration based on the large scale calibration target is provided.To avoid the shortcomings of the method, the vector differencesof reprojection error with the presence of the constraint conditionof the constant rigid body transformation is modelled, and mini-mized by the Levenberg-Marquardt （LM） method. Results of thesimulation and observation data calibration experiment show thatthe accuracy of the system calibrated by the proposed methodreaches 2 mm when measuring distance section of 20 000 mmand scale section of 7 000 mm × 7 000 mm. Consequently, theproposed method of multi-camera calibration performs better thanthe fundamental in stability. This technique offers a more uniformerror distribution for measuring large scale space.