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Filters
A Study on Local Variance Threshold Based Boundary Detector with Median Filter
2018
International Journal of Innovative Research in Electronics and Communications
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Image segmentation is made easy when the outer shape of the object is identified clearly. In this paper, the boundary detection is performed with the local variance of the pixels under calculation. ...
This paper investigates the boundary detection algorithm based on local variance threshold technique. ...
RESULTS In this paper, the local variance based object detector is used to detect the boundary of the objects in the image under denoised filtering. ...
doi:10.20431/2349-4050.0501002
fatcat:wzi7dtjof5aenn2cst6kaettgi
Recognition And Tracking Of Moving Object In Underwtaer Sonar Images
2016
International Journal of MC Square Scientific Research
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Underwater image processing for object recognition is a system which loads a image, pre-processes the image, filters and scales the image to find the object. ...
This paper presents an resourceful technique which can be used for underwater object recognition system computerization. ...
If the noise variance is not given, wiener2 uses the average of all the local estimated variances . 3. ...
doi:10.20894/ijmsr.117.008.001.010
fatcat:45yv5jymxfblhb5fgpkrqty6gq
Robust Method of Vote Aggregation and Proposition Verification for Invariant Local Features
2015
Proceedings of the 10th International Conference on Computer Vision Theory and Applications
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2016 pre-print arXiv:1601.00781v1 fatcat:idsaxcr63nakbemy2323sjjdbi
Cascade filters contain all of the minor algorithms needed for effective object detection verification. ...
This paper presents a method for analysis of the vote space created from the local features extraction process in a multi-detection system. ...
We used Good Features To Track by Tomasi and Shi (Shi and Tomasi, 1994) to detect multiple local maximas in the vote image and used them as the propositions. ...
doi:10.5220/0005267002520259
dblp:conf/visapp/KurzejamskiZS15
fatcat:vhklssfnqjedhjs2sxgtn6ltka
Robust multiple object tracking by detection with interacting Markov chain Monte Carlo
2013
2013 IEEE International Conference on Image Processing
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The local particle filter models the local motion of the object. The global particle filter models the interaction with the other objects and scene. ...
The proposed online tracking methodology could be scaled to hundreds of objects and could be completely parallelized. For every object, we have a set of two particle filters, i.e. local and global. ...
Acknowledgments We would like to thank Mei Jiang and David Williams from Jules Stein Eye Institute (UCLA) for providing Melanosomes data and ONR grant #N00014-12-1-0503. ...
doi:10.1109/icip.2013.6738608
dblp:conf/icip/SunderrajanKM13
fatcat:sis2upj3ibbgvmg75xvk5uaywa
Exposing image splicing with inconsistent local noise variances
2012
2012 IEEE International Conference on Computational Photography (ICCP)
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Our method estimates local noise variances based on an observation that kurtosis values of natural images in band-pass filtered domains tend to concentrate around a constant value, and is accelerated by ...
inconsistencies in local noise variances. ...
Zhouchen Lin for sharing with us the images and results from his work [16] , and and Dr. Babak Mahdian for sharing with us the MATLAB code of his work [22] . ...
doi:10.1109/iccphot.2012.6215223
dblp:conf/iccp/PanZL12
fatcat:yho2jyrzdng7xfpnhsw7cfvv6y
Defect detection in textured materials using optimized filters
2002
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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The problem of automated defect detection in textured materials is investigated. A new approach for defect detection using linear FIR filters with optimized energy separation is proposed. ...
The issues relating to the design of optimal filters for supervised and unsupervised web inspection are addressed. A general web inspection system based on the optimal filters is proposed. ...
Therefore an optimal filter should not only produce large separation of mean local energy estimate, but also yield low variances and . ...
doi:10.1109/tsmcb.2002.1033176
pmid:18244861
fatcat:t6rbfpfzl5cmhhknqrvrcdzjj4
A framework for robust object multi-detection with a vote aggregation and a cascade filtering
[article]
2015
arXiv
pre-print
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A high detection rate with a low false detection chance can be achieved with use of only one pattern per object and no manual parameters adjustments. ...
The framework uses a single feedback loop and a pattern resizing mechanism to demonstrate the top effectiveness of the state-of-the-art local features. ...
System uses local features and voting mechanism for localization and a cascade of filters to reject false detections presented in [16] . ...
arXiv:1512.08648v1
fatcat:35fpwuwmk5b3lb47rktzeerjke
Video Monitoring Queries
[article]
2020
arXiv
pre-print
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We propose two classes of filters IC and OD, that adapt principles from deep image classification and object detection. ...
The resulting filters are able to assess quickly if the query predicates are true to proceed with further analysis of the frame or otherwise not consider the frame further avoiding costly object detection ...
We demonstrate that this improves the detection and localization process, as the network is trained to recognize as well as localize objects from scratch. ...
arXiv:2002.10537v1
fatcat:piokyrprvjdh5hlrupz3a2atju
Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point Clouds
[article]
2020
arXiv
pre-print
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With a large perception range, we are able to capture the variance of features for potential objects and generate attentive spatial guidance to help adjust the strengths for different regions. ...
dynamic convolutional layer to adapt to the variance of input features by learning from local semantic context. ...
We use an auxiliary network to learn these coefficients based on local semantic context and perform position-dependent convolution to adapt to the variance on feature maps. ...
arXiv:1912.04775v3
fatcat:ln5cse3bgvbzbcygedqngkultq
SEGMENTING TAGGED CARDIAC MRI DATA USING A LOCAL VARIANCE FILTER
2014
Acta Polytechnica
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We estimate the intensity using a local variance filter. The main segmentation is computed by the graph-cuts method, though other segmentation methods can also be used. ...
a Local Variance Filter whether the given pixel belongs to object O and background P , respectively. ...
which we have adopted from [14] . ln P (I|O) and ln P (I|P ) are conditioned probabilities expressing vol. no. / Segmenting Tagged Cardiac MRI Data Using a Local Variance Filter Table 1 . ...
doi:10.14311/ap.2014.54.0214
fatcat:f6wghgk5sfbtnkhcu2zxim6iie
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain
2009
ELCVIA Electronic Letters on Computer Vision and Image Analysis
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These restoration algorithms take advantages of a space-time Wiener filter and a space-time regularization by the Laplacian operator. ...
It was shown that a gradation between Wiener and Laplacian areas improves results quality, so that only the algorithm using a gradation will be used in this article. ...
Yaroslavsky et al. first process and then fuse visible and thermal sequences to obtain better results [2] , or first use a median filter to obtain an unwarped image and then detect moving objects [3] ...
doi:10.5565/rev/elcvia.185
fatcat:wrv33zrfavey5px5tfkyastyaq
Minimal Weighted Local Variance as Edge Detector for Active Contour Models
[chapter]
2006
Lecture Notes in Computer Science
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The direction and magnitude of edges are estimated such that the minimal weighted local variance condition is satisfied. ...
Using the active contour methods, this paper proposes a new vector field for detection of such structures. ...
Yu of the Department of Diagnostic Radiology and Organ Imaging, Prince of Wales Hospital, Hong Kong, for providing the DSA images. ...
doi:10.1007/11612032_63
fatcat:3645ahfhprftzkanxjnonvocdy
Ghost and Noise Removal in Exposure Fusion for High Dynamic Range Imaging
2014
International Journal of Computer Graphics & Animation
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In high dynamic range (HDR) imaging, local motion of objects and noise in a set of LDRIs can influence a final HDRI: local motion of objects causes the ghost artifact and LDRIs, especially captured with ...
In this paper, we propose a ghost and noise removal method for HDRI using exposure fusion with subband architecture, in which Haar wavelet filter is used. ...
To detect object motion, a variance based method [2] uses the weighted variance of pixel values between multiple-exposure LDRIs and divides images by thresholding into two regions: motion region and ...
doi:10.5121/ijcga.2014.4401
fatcat:46yls3r44ngq5oxne4l2ft2k74
Filtering-Based Noise Estimation for Denoising the Image Degraded by Gaussian Noise
[chapter]
2011
Lecture Notes in Computer Science
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In addition, the modified Gaussian noise removal filter based on the local statistics such as local weighted mean, local weighted activity and local maximum is flexibly used to control the degree of noise ...
Experimental results show the competitive performance of the proposed filter algorithm compared to the other standard algorithms in terms of both subjective and objective evaluations. ...
In addition, the local weighted mean, local weighted variance and local weighted max play an significant role to the denoising stage since its' advantages [8] , [9] , we use them as the key factors to ...
doi:10.1007/978-3-642-25346-1_15
fatcat:aytgzncg5zcrvcggqva32qxusa
Fast Combined Separability Filter for Detecting Circular Objects
2011
IAPR International Workshop on Machine Vision Applications
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The evaluation experiments using synthetic images and real face images show that the proposed filter is 70 times faster than the conventional circular separability filter. ...
In this paper, we propose a fast combined separability filter, which can selectively detect circular features such as pupils and nostrils in an image of the human face. ...
The proposed method using the arithmetic mean, CSF, and SSF outputs many improper positions of high local maximum points such as at the center lines of the rectangular object. ...
dblp:conf/mva/OhkawaS11
fatcat:tia27jjmoff4jms55c5uhyh63a
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