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This paper aims to propose image stitching by reduction of full line and taking line image as registration image to solve the problem of automatic optic inspection in PCB detection. In addition, surf registration was introduced for image stitching to improve the accuracy and speed of stitching.

First, image stitching proceeded by method of full line reduction and taking line image as registration image; second, surf registration was introduced based on the traditional PCB image stitching algorithm. Scale space of the image pyramid was adopted for confirming relative future points between stitching image. The registration means of nearest neighbourhood and next neatest neighborhood was selected for feature matching and fused in region of interest to fulfil image stitching.

The improved stitching algorithm with small data size of image, high speed and noncumulative transitive error eliminated displacement deviation and solved the stitching gap caused by uneven illumination, to greatly improve the accuracy and speed of stitching.

The research of this paper can only used for appearance detection and cannot be used for solder joint inspection with circuit detection or invisible solder joint detection; it can identify and mark PCB component defects but cannot classify automatically, thus artificial confirmation and processing is needed.

Based on the traditional image stitching means, this paper proposed full line reduction for image stitching, which reduces processing of data and speeds up image stitching; in addition, surf registration was introduced into the study of PCB stitching algorithm, which greatly improves the accuracy and speed of stitching and solves stitching gap formed by opposite variation trend of image local edge caused by uneven illumination.

The purpose of this paper is to present weighted Euclidean distance for measuring whether the fitting of projective transformation matrix is more reliable in feature-based image stitching.

The hybrid model of weighted Euclidean distance criterion and intelligent chaotic genetic algorithm (CGA) is established to achieve a more accurate matrix in image stitching. Feature-based image stitching is used in this paper for it can handle non-affine situations. Scale invariant feature transform is applied to extract the key points, and the false points are excluded using random sampling consistency (RANSAC) algorithm.

This work improved GA by combination with chaos's ergodicity, so that it can be applied to search a better solution on the basis of the matrix solved by Levenberg-Marquardt. The addition of an external loop in RANSAC can help obtain more accurate matrix with large probability. Series of experimental results are presented to demonstrate the feasibility and effectiveness of the proposed approaches.

The modified feature-based method proposed in this paper can be easily applied to practice and can obtain a better image stitching performance with a good robustness.

A hybrid model of weighted Euclidean distance criterion and CGA is proposed for optimization of projective transformation matrix in image stitching. The authors introduce chaos theory into GA to modify its search strategy.

Sewing is the most widely used and preferred method for manufacturing clothing products for extreme weather conditions and other industrial insulation systems. Multiple layers of functional fabrics in combination with insulation materials are used to thermally insulate precious body heat from its surrounding cold environment. The sewing process fixes the insulation material between the fabric layers. During conventional sewing, the insulation material is compressed along the stitch line. With the compression of the insulation material, entrapped air is forced to leave the insulation material internal structure, and heat loss occurs along the entire length of the stitch line. It results in the deterioration of thermal properties of the end product along the stitch line.

The amount of air, which is a decisive factor for thermal properties of any insulation system, was investigated at the level of a unit stitch length of a lockstitch. Conventional microscopy methods are not suitable to study the compression along the stitch line. With the help of X-ray tomography, the three-dimensional data of a stitch was taken and studied to measure the volume of air. The samples were prepared with conventional lockstitch sewing and a newly developed innovative sewing method “Spacer Stitching.” The results are compared with each other in terms of the amount of air present in a unit stitch length.

Calculations based on X-ray tomography images of lockstitch and spacer stitch revealed that, in the case of lockstitch, a unit stitch has a 15% of its volume made up of material and 85% of its volume by air. In comparison, the spacer stitch with the same sewing and fabric parameters has a material volume of 4.6 % and an air volume of 95.4% in a single stitch.

The research can positively improve the thermal properties of sewn material made for insulating purposes of conventional clothing as well as of industrial insulations.

There is no literature available which investigates and calculates the amount of air and material present along with a stitch line.

The purpose of this paper is to analyze the development of a novel approach for automated terrain mapping a robotic vehicles path tracing.

The approach includes stitching of images, obtained from unmanned aerial vehicle, based on ORB descriptors, into an orthomosaic image and the GPS-coordinates are binded to the corresponding pixels of the map. The obtained image is fed to a neural network MASK R-CNN for detection and classification regions, which are potentially dangerous for robotic vehicles motion. To visualize the obtained map and obstacles on it, the authors propose their own application architecture. Users can any time edit the present areas or add new ones, which are not intended for robotic vehicles traffic. Then the GPS-coordinates of these areas are passed to robotic vehicles and the optimal route is traced based on this data

The developed approach allows revealing impassable regions on terrain map and associating them with GPS-coordinates, whereas these regions can be edited by the user.

The total duration of the algorithm, including the step with Mask R-CNN network on the same dataset of 120 items was 7.5 s.

Creating an orthophotomap from 120 images with image resolution of 470 × 425 px requires less than 6 s on a laptop with moderate computing power, what justifies using such algorithms in the field without any powerful and expensive hardware.

In a typical additive manufacturing (AM) system, it is critical to make a trade-off between the resolution and the build area for applications in which varied dimensions, feature sizes and accuracies are desired. Conventional solutions to this challenge are based on curing of multiple areas with a single high resolution and stitching them to form a large layer. However, because of the lack of the capability in adjusting resolution dynamically, such stitching approaches will elongate the build time greatly in some cases. To address the challenge without sacrificing the build speed, this paper aims to design and develop a novel AM system with dynamic resolution control capability.

A laser projector is adopted in a vat photopolymerization system. The laser projection system has unique properties, including focus-free operation and capability to produce dynamic mask image irrespective of any surface (flat or curved). By translating the projector along the building direction, the pixel size can be adjusted dynamically within a certain range. Consequently, the build area and resolution could be tuned dynamically in the hardware testbed. Besides, a layered depth image (LDI) algorithm is used to construct mask images with varied resolutions. The curing characteristics under various resolution settings are quantified, and accordingly, a process planning approach for fabricating models with dynamically controlled resolutions is developed.

A laser projection-based stereolithography (SL) system could tune resolution dynamically during the building process. Such a dynamic resolution control approach completely addresses the build size-resolution dilemma in vat photopolymerization AM processes without sacrificing the build speed. Through fabricating layers with changing resolutions instead of a single resolution, various build areas and feature sizes could be produced precisely, with optimized build speed.

A focus-free laser projector is investigated and adopted in a SL system for the first time. The material curing characteristics with changing focal length and therefore changing light intensities are explored. The related digital mask image planning and process control methods are developed. In digital mask image planning, it is the first attempt to adopt the LDI algorithm, to identify proper resolution settings for fabricating a sliced layer precisely and quickly. In the process of characterizing material curing properties, parametric dependence of curing properties on focal length has been unveiled. This research contributes to the advancement of AM by addressing the historical dilemma of the resolution and build size, and optimizing the build speed meanwhile.

This paper aims to present a mosaicking method for underwater robotic applications, whose result can be provided to other perceptual systems for scene understanding such as real-time object recognition.

This method is called robust and large-scale mosaicking (ROLAMOS) and presents an efficient frame-to-frame motion estimation with outlier removal and consistency checking that maps large visual areas in high resolution. The visual mosaic of the sea-floor is created on-the-fly by a robust registration procedure that composes monocular observations and manages the computational resources. Moreover, the registration process of ROLAMOS aligns the observation to the existing mosaic.

A comprehensive set of experiments compares the performance of ROLAMOS to other similar approaches, using both data sets (publicly available) and live data obtained by a ROV operating in real scenes. The results demonstrate that ROLAMOS is adequate for mapping of sea-floor scenarios as it provides accurate information from the seabed, which is of extreme importance for autonomous robots surveying the environment that does not rely on specialized computers.

The ROLAMOS is suitable for robotic applications that require an online, robust and effective technique to reconstruct the underwater environment from only visual information.

FOV splicing optical remote sensing instruments have a strict requirement for the focal length consistency of the lens. In conventional optical-mechanical structure design, each optical element is equally distributed with high accuracy and everyone must have a high machining and assembly accuracy. For optical remote sensors with a large number of optical elements, this design brings great difficulties to lens manufacture and alignment.

Taking the relay lens in an optical remote sensing instrument with the field of view splicing as an example, errors of the system are redistributed to optical elements. Two optical elements, which have the greatest influence on modulation transfer function (MTF) of the system are mounted with high accuracy centering and the other elements are fixed by gland ring with common machining accuracy. The reduction ratio consistency difference among lenses is compensated by adjusting the optical spacing between the two elements.

Based on optical system simulation analysis, the optimized structure can compensate for the difference of reduction ratio among lens by grinding the washer thickness in the range of ±0.37 mm. The test data for the image quality of the lens show that the MTF value declined 0.043 within ±0.4 mm of space change between two barrels. The results indicate that the reduction ratio can be corrected by adjusting the washer thickness and the image quality will not obviously decline.

This paper confirms that this work is original and has not been published elsewhere nor is it currently under consideration for publication elsewhere. In this paper, the optimum structural design of the reduction relay lens for the field of view stitching applications is reported. The method of adjusting washer thickness is applied to compensate for the reduction ratio consistency difference of lenses. The optimized structure also greatly reduces the difficulty of lenses manufacture, alignment and improves the efficiency of assembly.

The purpose of this paper is to describe how the authors designed a small satellite formation ground test bed in order to study the small satellite formation flying technologies, such as autonomous formation control and network communication. As one of the subsystems, the vision detection system is responsible for the pose (position and orientation) detection of the three small satellite simulators, each of which is composed of a wheeled mobile robot and an on‐board micro control unit. In this paper, the rapid vision locating of the three small satellite simulators in the wide field is discussed.

The scene size required by the test bed has exceeded the scope of one camera, thus how to obtain the complete scene becomes a difficulty. On the base of image mosaic, a vision system composed of two cameras is designed to capture the scene simultaneously. After the two overlapped images are rapidly stitched, the real‐time view of the big scene is attained. Second, the new color tag representing the pose of small satellite simulators is designed, which can be easily identified.

A real‐time multiple mobile robots visual locating system is introduced, in which the global search algorithm and track search algorithm are combined together to identify the real‐time pose of multiple mobile robots. The switching strategy between the two algorithms is given to ensure the accuracy and improve retrieval speed.

The paper shows how, without camera calibration, the pose of each small satellite simulator in the world coordinate system can be directly calculated by the coordinate transformation from the image coordinate system to the world coordinate system based on relative measurement. The accuracy and real‐time performance of the vision detection system have been validated by experiments on locating static tags and dynamic tracking three small satellite simulators.

Periodic inspection of large tonnage vessels is critical to assess integrity and prevent structural failures that could have catastrophic consequences for people and the environment. Currently, inspection operations are undertaken by human surveyors, often in extreme conditions. This paper aims to present an innovative system for the automatic visual inspection of ship hull surfaces, using a magnetic autonomous robotic crawler (MARC) equipped with a low-cost monocular camera.

MARC is provided with magnetic tracks that make it able to climb along the vertical walls of a vessel while acquiring close-up images of the traversed surfaces. A homography-based structure-from-motion algorithm is developed to build a mosaic image and also produce a metric representation of the inspected areas. To overcome low resolution and perspective distortion problems in far field due to the tilted and low camera position, a “near to far” strategy is implemented, which incrementally generates an overhead view of the surface, as long as it is traversed by the robot.

This paper demonstrates the use of an innovative robotic inspection system for automatic visual inspection of vessels. It presents and validates through experimental tests a mosaicking strategy to build a global view of the structure under inspection. The use of the mosaic image as input to an automatic corrosion detector is also demonstrated.

This paper may help to automate the inspection process, making it feasible to collect images from places otherwise difficult or impossible to reach for humans and automatically detect defects, such as corroded areas.

This paper provides a useful step towards the development of a new technology for automatic visual inspection of large tonnage ships.

This paper investigates and illustrates the potential of using panorama virtual reality to enhance Web‐based library instruction. It describes a project in Sterling C. Evans Library at Texas A&M University that emulates a physical tour and renders it into an attention‐getting virtual tour with 360‐degree realistic views. The paper outlines three progressive developments in the use of tour as an instructional medium: the “physical tour”, the “Web virtual tour”, and the “virtual reality tour”. The project illustrates that panorama VR could be a powerful tool to combine the “physical tour” and the “Web‐based virtual tour” into one, making it a more useful medium that allows navigating, viewing, reading, hearing and remote access. The issues of design, hardware, software, and cost are addressed. The discussion also includes an overview of the Internet‐based VR technologies, a literature review of using VR technologies for learning and some considerations on future applications of panorama‐based virtual reality.