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Texture Complexity Based Redundant Regions Ranking for Object Proposal
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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In this paper, we propose a strategy named Texture Complexity based Redundant Regions Ranking (TCR) for object proposal. ...
It then uses Texture Complexity (TC) based on complete contour number and Local Binary Pattern (LBP) entropy to measure the objectness score of each region. ...
We propose a strategy named Texture Complexity based Redundant Regions Ranking (TCR) for object proposal. Our approach first produces redundant regions using Selective Search. ...
doi:10.1109/cvprw.2016.139
dblp:conf/cvpr/KeZCWYH16
fatcat:hsk6ylfmi5hajcoskta4q34lvm
Image Inpainting Algorithm Based on Low-Rank Approximation and Texture Direction
2014
Mathematical Problems in Engineering
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Existing image inpainting algorithm based on low-rank matrix approximation cannot be suitable for complex, large-scale, damaged texture image. ...
An inpainting algorithm based on low-rank approximation and texture direction is proposed in the paper. At first, we decompose the image using low-rank approximation method. ...
In this paper, we propose a new image restoration algorithm based on matrix low-rank approximation. ...
doi:10.1155/2014/621520
fatcat:x3jzdsveq5dppnm5mgwjf6btbu
Defect detection for patterned fabric images based on GHOG and low-rank decomposition
2019
IEEE Access
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In this paper, a novel patterned method for fabric defect detection is proposed based on a novel texture descriptor and the low-rank decomposition model. ...
In this paper, a novel patterned method for fabric defect detection is proposed based on a novel texture descriptor and the low-rank decomposition model. ...
Machine vision based methods for fabric defect detection should be designed based on the features of fabric images, e.g., their texture. ...
doi:10.1109/access.2019.2925196
fatcat:vlgoswnubra75jf6mawkqkqt54
Combination of Spatial and Frequency Domains for Floating Object Detection on Complex Water Surfaces
2019
Applied Sciences
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It adopts global and local low-rank decompositions to remove redundant regions caused by multiple interferences and retain floating objects. ...
Then, a novel frequency-based saliency detection method used in complex scenes is proposed. ...
Acknowledgments: The authors are grateful for the experimental platform and resources provided by the Sichuan Province Key Laboratory of Special Environmental Robotics. ...
doi:10.3390/app9235220
fatcat:gsl6zzbfynefxcayxecppgzyxy
Complexity-adaptive distance metric for object proposals generation
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Distance metric plays a key role in grouping superpixels to produce object proposals for object detection. We observe that existing distance metrics work primarily for low complexity cases. ...
In this paper, we develop a novel distance metric for grouping two superpixels in high-complexity scenarios. ...
Proposals ranking The proposals produced above may contain a large number of redundant regions, such as single superpixel within the background. ...
doi:10.1109/cvpr.2015.7298678
dblp:conf/cvpr/XiaoLTLT15
fatcat:pz7jqcslojgdxfo6njcgeyjeoq
Human-centric approaches to image understanding and retrieval
2010
2010 Western New York Image Processing Workshop
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A key goal of recent researches on image retrieval is to develop retrieval systems that respond to individual user's query for real time applications. ...
Such a speculative development in this field can be attained through more effective approaches with reduced computational complexity and increased/enhanced retrieval accuracy. ...
It allows an object To tackle the problem of time and computational to be distinguished from its surroundings by its outline. complexity, an effective method based on region codes to Classically available ...
doi:10.1109/wnyipw.2010.5649743
fatcat:tej3mc24ffgppa7aop4ea5qmku
Eurécom at TRECVid 2006: Extraction of High-level Features and BBC Rushes Exploitation
2006
TREC Video Retrieval Evaluation
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This year's run is based on a SVM classification scheme. Localised color and texture features were extracted from shot key-frames. ...
A set of non-redundant images are segmented into blocks. These blocks are clustered in a small number of classes to create a visual dictionary. ...
We then propose to build two rectangular regions around each salient point, one region on the left and the other on the right for vertical edges and one on the top and the other on the bottom for horizontal ...
dblp:conf/trecvid/BenmokhtarDHM06
fatcat:p24pb2bcgbbp7jdqyvbf3ntxdu
Double Low-rank Based Matrix Decomposition for Surface Defect Segmentation of Steel Sheet
2021
ISIJ International
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be represented as a combination of a highly redundant part (i.e., visually consistent background regions) and a sparse part (i.e., foreground object regions). ...
These methods don't consider the low-rank characteristic for defect foreground object and background regions simultaneously, and ignore the spatial and pattern relations of image regions, which may influence ...
doi:10.2355/isijinternational.isijint-2021-024
fatcat:v2biyp6jojcvhdlzbit67ymz4y
Fabric defect detection based on deep-feature and low-rank decomposition
2020
Journal of Engineered Fibers and Fabrics
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In this article, a novel fabric defect detection algorithm is proposed based on a multi-scale convolutional neural network and low-rank decomposition model. ...
Finally, the saliency maps generated by the sparse matrix are segmented based on an improved optimal threshold to locate the fabric defect regions. ...
Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science
ORCID ...
doi:10.1177/1558925020903026
fatcat:culdptirtnbjfhj2t55jhagwly
A comparative analysis of various approaches used for feature extraction in content based image retrieval
2016
International Journal of Advanced Research
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region-based involves The internal features of the region selected. ...
[6] Shape representations can be generally divided into two categories: Boundary-based, and region-based:-0 Boundary based involves the external features or pixels at outer boundary of the object, whereas ...
doi:10.21474/ijar01/1154
fatcat:g5uztqsdjnd2joaakyqu2fruz4
Content-based image retrieval with the normalized information distance
2008
Computer Vision and Image Understanding
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., color, shape, texture) are extracted from each image and organized into a feature vector. ...
Using those approximations, the NID between images is calculated and used as a metric for CBIR. ...
., [12] ) have been proposed that can learn object categories. ...
doi:10.1016/j.cviu.2007.11.001
fatcat:apszuaurknaypmsexvtoqo6aqm
A Flexible Lossy Depth Video Coding Scheme Based on Low-rank Tensor Modelling and HEVC Intra Prediction for Free Viewpoint Video
[article]
2021
arXiv
pre-print
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In this paper, we introduce a novel low-complexity scheme for depth video compression based on low-rank tensor decomposition and HEVC intra coding. ...
The proposed scheme leverages spatial and temporal redundancy by compactly representing the depth sequence as a high-order tensor. ...
In this paper, we introduce a novel low-complexity scheme for depth video compression based on low-rank tensor decomposition and HEVC intra coding. ...
arXiv:2104.04678v1
fatcat:qjadbghnqzckjcjkxilqp5tbve
Logo detection based on spatial-spectral saliency and partial spatial context
2009
2009 IEEE International Conference on Multimedia and Expo
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Based on key traits analysis of common logos, this paper presents a two-stage detection scheme based on spatialspectral saliency (SSS) and partial spatial context (PSC). ...
The results indicate that our method is applicable and precise for different logo detection scenarios. ...
Bag-of-local-features (BOF) based image representation is also proposed for object detection [15] . ...
doi:10.1109/icme.2009.5202500
dblp:conf/icmcs/GaoLZTZ09
fatcat:uuvb2frgvjh7tmvb6nbkc4nula
Earthquake-Induced Building-Damage Mapping Using Explainable AI (XAI)
2021
Sensors
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Further, spectral features are found to be more important than texture features in distinguishing the collapsed and non-collapsed buildings. ...
The results show that MLP can classify the collapsed and non-collapsed buildings with an overall accuracy of 84% after removing the redundant features. ...
Furthermore, redundant features may add a layer of complexity to the model and thus, decrease the accuracy [45] . ...
doi:10.3390/s21134489
pmid:34209169
pmcid:PMC8271973
fatcat:htfgam6hwjgv5foz2m5lz6p45y
Multi-objectives optimization of features selection for the classification of thyroid nodules in ultrasound images
2020
IET Image Processing
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Their proposed CAD has reached a maximum accuracy of 94.28% for SVM; and 96.13% for RF using the contour-based ROI. ...
A feature selection method based on the multi objective particle swarm optimisation algorithm was used to choose the most relevant and non-redundant ones. ...
Singh and Jindal [3] have developed a method for the classification of thyroid nodules based on texture analysis. ...
doi:10.1049/iet-ipr.2019.1540
fatcat:uoqwzl25xjbprexdo2q2pe7ore
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