scholarly journals PHOTOMATCH: AN OPEN-SOURCE MULTI-VIEW AND MULTI-MODAL FEATURE MATCHING TOOL FOR PHOTOGRAMMETRIC APPLICATIONS

2020 ◽  
Vol XLIII-B5-2020 ◽  
pp. 213-219 ◽  
Author(s):  
D. González-Aguilera ◽  
E. Ruiz de Oña ◽  
L. López-Fernandez ◽  
E. M. Farella ◽  
E. K. Stathopoulou ◽  
...  
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Image Matching ◽  
Historical Perspective ◽  
Feature Matching ◽  
Enabling Technology ◽  
Crucial Step ◽  
Research Activities ◽  
Quality Control Metrics ◽  
Automated Pipeline

Abstract. Automatic feature matching is a crucial step in Structure-from-Motion (SfM) applications for 3D reconstruction purposes. From an historical perspective we can say now that SIFT was the enabling technology that made SfM a successful and fully automated pipeline. SIFT was the ancestor of a wealth of detector/descriptor methods that are now available. Various research activities have tried to benchmark detector/descriptors operators, but a clear outcome is difficult to be drawn. This paper presents an ISPRS Scientific Initiative aimed at providing the community with an educational open-source tool (called PhotoMatch) for tie point extractions and image matching. Several enhancement and decolorization methods can be initially applied to an image dataset in order to improve the successive feature extraction steps. Then different detector/descriptor combinations are possible, coupled with different matching strategies and quality control metrics. Examples and results show the implemented functionality of PhotoMatch which has also a tutorial for shortly explaining the implemented methods.

Rapid mapping accuracy assessment using low-cost UAV and open-source Structure from Motion

2020 ◽  
Vol 52 ◽  
pp. 55-61
Author(s):  
Ettore Potente ◽  
Cosimo Cagnazzo ◽  
Alessandro Deodati ◽  
Giuseppe Mastronuzzi
Keyword(s):  
Open Source ◽  
Structure From Motion ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Mapping Accuracy ◽  
Rapid Mapping ◽  
Source Structure

Identification of the Hook on Investment Casting Shell Line Based on Machine Vision

2012 ◽  
Vol 220-223 ◽  
pp. 1356-1361
Author(s):  
Xi Jie Tian ◽  
Jing Yu ◽  
Chang Chun Li
Keyword(s):  
Machine Vision ◽  
Investment Casting ◽  
Hough Transform ◽  
Image Matching ◽  
Feature Matching ◽  
Image Acquisition ◽  
Target Range ◽  
Target Area ◽  
Matching Method ◽  
Vertical Projection

In this paper, the idea identify the hook on investment casting shell line based on machine vision has been proposed. According to the characteristic of the hook, we do the image acquisition and preprocessing, we adopt Hough transform to narrow the target range, and find the target area based on the method combining the level projection and vertical projection, use feature matching method SIFT to do the image matching. Finally, we get the space information of the target area of the hook.

Two-Dimensional Image Based Product Connector Recognition for Robotic Disassembly in Remanufacturing

2021 ◽  
Author(s):  
Yang Hu ◽  
Yalin Wang ◽  
Feng Xu ◽  
Bitao Yao ◽  
Wenjun Xu ◽  
...  
Keyword(s):  
Template Matching ◽  
Search Strategy ◽  
Feature Matching ◽  
Resource Conservation ◽  
Recognition Algorithm ◽  
Two Dimensional ◽  
Crucial Step ◽  
Two Dimensional Image ◽  
Disassembly Process ◽  
Robotic Disassembly

Abstract Remanufacturing has received increasing attention for environmental protection and resource conservation considerations. Disassembly is a crucial step in remanufacturing, is always done manually which is inefficient while robotic disassembly can improve the efficiency of the disassembly. Aiming at the problem of product connector recognition during the robotic disassembly process, we analyze the template matching and feature matching principles based on two-dimensional images. To reduce the computational complexity of traditional template matching, a stepwise search strategy combining coarse and fine is proposed. Based on this a product connector recognition algorithm based on fast template matching and a product connector recognition algorithm based on feature matching is designed. Taking bolts and hexagon nuts as examples, the recognition effects of the two algorithms are compared and analyzed.

Implementation of Verification and Matching E-KTP with Faster R-CNN and ORB

2021 ◽  
Vol 5 (4) ◽  
pp. 783-793
Author(s):  
Muhammad Muttabi Hudaya ◽  
Siti Saadah ◽  
Hendy Irawan
Keyword(s):  
Image Matching ◽  
Nearest Neighbor ◽  
Feature Matching ◽  
Image Feature ◽  
Brute Force ◽  
K Nearest Neighbor ◽  
Matching Method ◽  
Average Precision ◽  
Detection Model ◽  
Matching Process

needs a solid validation that has verification and matching uploaded images. To solve this problem, this paper implementing a detection model using Faster R-CNN and a matching method using ORB (Oriented FAST and Rotated BRIEF) and KNN-BFM (K-Nearest Neighbor Brute Force Matcher). The goal of the implementations is to reach both an 80% mark of accuracy and prove matching using ORB only can be a replaced OCR technique. The implementation accuracy results in the detection model reach mAP (Mean Average Precision) of 94%. But, the matching process only achieves an accuracy of 43,46%. The matching process using only image feature matching underperforms the previous OCR technique but improves processing time from 4510ms to 60m). Image matching accuracy has proven to increase by using a high-quality dan high quantity dataset, extracting features on the important area of EKTP card images.

scholarly journals Hybrid Invariant Local Features for Multiple Satellite Image Matching and Registration

2019 ◽  
Vol 9 (2) ◽  
pp. 309-314
Keyword(s):  
Image Matching ◽  
Feature Matching ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Local Features ◽  
Feature Descriptor ◽  
Matching Method ◽  
Multiple Images ◽  
Feature Sets ◽  
Precise Relationship

Automatic image registration (IR) is very challenging and very important in the field of hyperspectral remote sensing data. Efficient autonomous IR method is needed with high precision, fast, and robust. A key operation of IR is to align the multiple images in single co-ordinate system for extracting and identifying variation between images considered. In this paper, presented a feature descriptor by combining features from both Feature from Accelerated Segment Test (FAST) and Binary Robust Invariant Scalable Key point (BRISK). The proposed hybrid invariant local features (HILF) descriptor extract useful and similar feature sets from reference and source images. The feature matching method allows finding precise relationship or matching among two feature sets. An experimental analysis described the outcome BRISK, FASK and proposed HILF in terms of inliers ratio and repeatability evaluation metrics.

scholarly journals SDR Enabled C-RAN Implementation using OpenAirInterface

2021 ◽  
Author(s):  
Akeem Olapade Mufutau ◽  
Fernando Pedro Guiomar ◽  
Arnaldo Oliveira ◽  
Paulo Pereira Monteiro
Keyword(s):  
Open Source ◽  
Software Defined Radio ◽  
Cellular Network ◽  
Access Network ◽  
Mobile Network ◽  
Radio Access Network ◽  
Research Activities ◽  
Radio Access ◽  
Continuous Dynamic ◽  
Cloud Ran

Abstract Towards enabling 5G radio access technologies and beyond to meet the requirements for continuous dynamic and diverse services, flexibility and scalability of the cellular network are therefore pertinent. The utilization of software-defined radio (SDR) aided with an open-source platform and virtualization techniques are increasingly exposing the realization of desirable flexibility for radio access network (RAN) while enabling the development of a prototype which can be directed at fostering further mobile network research activities. In this paper, we review OpenAirInterface (OAI) implementation and present an OAI based cloud RAN (C-RAN) testbed with which mobile fronthaul (MFH) solutions can be tested.

Taming of ‘Openness' in Software Innovation Systems

2017 ◽  
Vol 8 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Mehmet Gencer ◽  
Beyza Oba
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Open Innovation ◽  
Large Scale ◽  
Historical Perspective ◽  
Systems Of Innovation ◽  
Innovation Potential ◽  
Emergent Community ◽  
Strategic Pattern ◽  
The Continuum

In large-scale open source software (OSS) innovation ecosystems that incorporate firms, a variety of measures are taken to tame the potentially chaotic activities and align the contributions of various participants with the strategic priorities of major stakeholders. Such taming rests on the dual desires of this emergent community of firms to unleash the innovation potential of OSS and to drive it to a certain direction, and it emerges in the form of various organizational activities. By drawing on a sample of large-scale OSS ecosystems, the authors discuss that methods employed for taming are isomorphic, and overview the emerging strategic pattern for establishing systems of innovation. This pattern involves a related set of practices to balance virtues of OSS community while introducing corporate discipline. In contrast to approaches such as open innovation, which favor isolated reasoning, they present a systemic and historical perspective to explain the continuum in emergence and establishment of strategic patterns.

scholarly journals EMCM: A Novel Binary Edge-Feature-Based Maximum Clique Framework for Multispectral Image Matching

2019 ◽  
Vol 11 (24) ◽  
pp. 3026
Author(s):  
Bin Fang ◽  
Kun Yu ◽  
Jie Ma ◽  
Pei An
Keyword(s):  
Image Matching ◽  
Nearest Neighbor ◽  
Feature Matching ◽  
Maximum Clique ◽  
Feature Space ◽  
Multispectral Image ◽  
Feature Descriptor ◽  
Ranking Algorithm ◽  
Feature Based ◽  
Edge Feature

Seeking reliable correspondence between multispectral images is a fundamental and important task in computer vision. To overcome the nonlinearity problem occurring in multispectral image matching, a novel, edge-feature-based maximum clique-matching frame (EMCM) is proposed, which contains three main parts: (1) a novel strong edge binary feature descriptor, (2) a new correspondence-ranking algorithm based on keypoint distinctiveness analysis algorithms in the feature space of the graph, and (3) a false match removal algorithm based on maximum clique searching in the correspondence space of the graph considering both position and angle consistency. Extensive experiments are conducted on two standard multispectral image datasets with respect to the three parts. The feature-matching experiments suggest that the proposed feature descriptor is of high descriptiveness, robustness, and efficiency. The correspondence-ranking experiments validate the superiority of our correspondences-ranking algorithm over the nearest neighbor algorithm, and the coarse registration experiments show the robustness of EMCM with varied interferences.

Tool-Support for Software Development Processes

2010 ◽  
pp. 213-231 ◽  
Author(s):  
Marco Kuhrmann ◽  
Georg Kalus ◽  
Gerhard Chroust
Keyword(s):  
Software Development ◽  
Human Factors ◽  
Open Source ◽  
Development Process ◽  
Process Models ◽  
Tool Support ◽  
Development Projects ◽  
Crucial Step ◽  
Development Processes ◽  
The Many

Software development projects are complex. The more complex a project is, the higher are the requirements related to the software development process. The implementation of a process is a great challenge. This, in part, has to do with human factors (acceptance, etc.) as the benefits of a formal development process might not be obvious immediately and it may take a while until the process becomes the lifeblood of a team. A crucial step towards implementing, enacting and enforcing a process is to provide tool support for the many activities the process asks for. Tool support is necessary to guarantee efficiency in the project, to do the housekeeping and to minimize the “overhead” of the process. This chapter describes challenges and options for supporting process models by tools. Furthermore it describes concrete samples and shows how tool chains can be created with commercial tools as well as with open source tools.

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