scholarly journals PERBANDINGAN KOMBINASI METODE TEMPLATE MATCHING DAN ALGORITMA FEATURE MATCHING PADA PENGENALAN MATA UANG INDIA

2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Dwiki Aditama Supangkat ◽  
Fahmi Nugroho Alibasyah ◽  
Muhammad Rif'an Dzulqornain ◽  
Muhammad Hilal ◽  
Muhammad Atay Nadhif Nashrulloh ◽  
...  
Keyword(s):  
Template Matching ◽  
Feature Matching

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.

scholarly journals Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2319
Author(s):  
Chaofeng Ren ◽  
Junfeng Xie ◽  
Xiaodong Zhi ◽  
Yun Yang ◽  
Shuai Yang
Keyword(s):  
Template Matching ◽  
Feature Matching ◽  
Image Data ◽  
Stereo Image ◽  
Laser Altimeter ◽  
Spot Center ◽  
Brightness Difference ◽  
Least Squares Adjustment ◽  
Spot Image ◽  
Image Position

The Gaofen-7 (GF-7) satellite is equipped with two area array sensor footprint cameras to capture the laser altimeter spot. In order to establish a direct correspondence between the laser data and the stereo image data, a new method is proposed to fit the center of the spot using the brightness difference between the spot image and the footprint image. First, the geometric registration between the spot image and the footprint image is completed based on feature matching or template matching. Then, the brightness values between the two images are extracted from the corresponding image position to form a measurement, and the least squares adjustment method is used to calculate the parameters of the brightness conversion model between the spot image and the footprint image. Finally, according to the registration relationship, the center of the identified spots is respectively positioned in the footprint images, so that the laser spots are accurately identified in the along-track stereo footprint images. The experimental results show that the spot error of this method is less than 0.7 pixel, which has higher reliability and stability, and can be used for a GF-7 satellite footprint camera.

scholarly journals ADVANCED TIE FEATURE MATCHING FOR THE REGISTRATION OF MOBILE MAPPING IMAGING DATA AND AERIAL IMAGERY

2016 ◽  
Vol XLI-B1 ◽  
pp. 617-623
Author(s):  
P. Jende ◽  
M. Peter ◽  
M. Gerke ◽  
G. Vosselman
Keyword(s):  
Urban Areas ◽  
Template Matching ◽  
Feature Detection ◽  
Feature Matching ◽  
Aerial Imagery ◽  
Exterior Orientation ◽  
Mobile Mapping ◽  
Positioning Systems ◽  
Matching Techniques ◽  
Orientation Parameters

Mobile Mapping’s ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform’s position. Consequently, acquired data products’ positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. <br><br> We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. <br><br> This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images’ geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. <br><br> Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability of putative matches and the utilisation of templates instead of feature descriptors. In our experiments discussed in this paper, typical urban scenes have been used for evaluating the proposed method. Even though no additional outlier removal techniques have been used, our method yields almost 90% of correct correspondences. However, repetitive image patterns may still induce ambiguities which cannot be fully averted by this technique. Hence and besides, possible advancements will be briefly presented.

scholarly journals FEATURE MATCHING ENHANCEMENT OF UAV IMAGES USING GEOMETRIC CONSTRAINTS

2018 ◽  
Vol XLII-1 ◽  
pp. 307-314
Author(s):  
H. M. Mohammed ◽  
N. El-Sheimy
Keyword(s):  
Fundamental Matrix ◽  
Template Matching ◽  
Feature Matching ◽  
Image Features ◽  
Geometric Constraints ◽  
Least Square ◽  
Scene Structure ◽  
Feature Correspondences ◽  
Epipolar Constraints ◽  
Uav Images

<p><strong>Abstract.</strong> Preliminary matching of image features is based on the distance between their descriptors. Matches are further filtered using RANSAC, or a similar method that fits the matches to a model; usually the fundamental matrix and rejects matches not belonging to that model. There are a few issues with this scheme. First, mismatches are no longer considered after RANSAC rejection. Second, RANSAC might fail to detect an accurate model if the number of outliers is significant. Third, a fundamental matrix model could be degenerate even if the matches are all inliers. To address these issues, a new method is proposed that relies on the prior knowledge of the images’ geometry, which can be obtained from the orientation sensors or a set of initial matches. Using a set of initial matches, a fundamental matrix and a global homography can be estimated. These two entities are then used with a detect-and-match strategy to gain more accurate matches. Features are detected in one image, then the locations of their correspondences in the other image are predicted using the epipolar constraints and the global homography. The feature correspondences are then corrected with template matching. Since global homography is only valid with a plane-to-plane mapping, discrepancy vectors are introduced to represent an alternative to local homographies. The method was tested on Unmanned Aerial Vehicle (UAV) images, where the images are usually taken successively, and differences in scale and orientation are not an issue. The method promises to find a well-distributed set of matches over the scene structure, especially with scenes of multiple depths. Furthermore; the number of outliers is reduced, encouraging to use a least square adjustment instead of RANSAC, to fit a non-degenerate model.</p>

Study on the reform of “online and offline” mixed music education model under the 5G of the times

2021 ◽  
pp. 002072092098607
Author(s):  
Xiao Yuqing
Keyword(s):  
Big Data ◽  
Music Education ◽  
Information Fusion ◽  
Information Integration ◽  
Template Matching ◽  
Feature Matching ◽  
Feature Fusion ◽  
Data Simulation ◽  
Education Resources ◽  
Education Model

In order to improve the ability of “online and offline” mixed music education integration and information fusion under the background of 5G times, combined with the big data information processing method to reform the educational model, this paper proposes an optimization fusion method of “online and offline” mixed music education model under the background of 5G times based on multi-dimensional association feature fusion and cluster analysis. Establishing “online and offline” mixed music education resources big data information collection model, combining association rule mining method to “online and offline” mixed music education resources information mining and big data fusion processing, using fuzzy information clustering method to collect “online and offline” mixed music education resources information grid region clustering, through statistical analysis method to establish “online and offline” mixed music education information template matching model, Combined with multi-dimensional association feature fusion and spatial reconstruction technology for 5G era background “online and offline” mixed music education resources information integration and pattern recognition, Carry out the reform of “online and offline” mixed music education mode under the background 5G times under the environment of big data. Simulation results show that the “online and offline” mixed music education resources integration performance is better under the background of 5G, the feature matching ability is stronger, the data mining and information fusion degree is higher, which improves the reliability and mode optimization of mixed music education.

scholarly journals ADVANCED TIE FEATURE MATCHING FOR THE REGISTRATION OF MOBILE MAPPING IMAGING DATA AND AERIAL IMAGERY

2016 ◽  
Vol XLI-B1 ◽  
pp. 617-623 ◽  
Author(s):  
P. Jende ◽  
M. Peter ◽  
M. Gerke ◽  
G. Vosselman
Keyword(s):  
Urban Areas ◽  
Template Matching ◽  
Feature Detection ◽  
Feature Matching ◽  
Aerial Imagery ◽  
Exterior Orientation ◽  
Mobile Mapping ◽  
Positioning Systems ◽  
Matching Techniques ◽  
Orientation Parameters

Mobile Mapping’s ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform’s position. Consequently, acquired data products’ positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. &lt;br&gt;&lt;br&gt; We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. &lt;br&gt;&lt;br&gt; This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images’ geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. &lt;br&gt;&lt;br&gt; Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability of putative matches and the utilisation of templates instead of feature descriptors. In our experiments discussed in this paper, typical urban scenes have been used for evaluating the proposed method. Even though no additional outlier removal techniques have been used, our method yields almost 90% of correct correspondences. However, repetitive image patterns may still induce ambiguities which cannot be fully averted by this technique. Hence and besides, possible advancements will be briefly presented.

Word-Finding Support From Mobile Technology Benefits a Woman With Aphasia

2015 ◽  
Vol 24 (1) ◽  
pp. 26-39 ◽  
Author(s):  
Yvonne Gillette
Keyword(s):  
Mobile Technology ◽  
Clinical Education ◽  
Augmentative And Alternative Communication ◽  
Feature Matching ◽  
Mobile Technologies ◽  
Alternative Communication ◽  
Alternative Intervention ◽  
Communication Assessment ◽  
Word Finding ◽  
Intervention Costs

Mobile technology provides a solution for individuals who require augmentative and alternative intervention. Principles of augmentative and alternative communication assessment and intervention, such as feature matching and the participation model, developed with dedicated speech-generating devices can be applied to these generic mobile technologies with success. This article presents a clinical review of an adult with aphasia who reached her goals for greater communicative participation through mobile technology. Details presented include device selection, sequence of intervention, and funding issues related to device purchase and intervention costs. Issues related to graduate student clinical education are addressed. The purpose of the article is to encourage clinicians to consider mobile technology when intervening with an individual diagnosed with mild receptive and moderate expressive aphasia featuring word-finding difficulties.

Recognition of Birds in Blurred and Illumination Images by Local Features

2017 ◽  
Vol 7 (7) ◽  
pp. 243
Author(s):  
Suresha .M ◽  
. Sandeep
Keyword(s):  
Computer Vision ◽  
Time Complexity ◽  
Feature Detection ◽  
Feature Matching ◽  
Fast Algorithms ◽  
Local Features ◽  
Experimental Demonstration ◽  
Harris Corner ◽  
Blurred Image ◽  
Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.

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