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1
April 2010
MVHI '10: Proceedings of the 2010 International Conference on Machine Vision and Human-machine Interface
Publisher: IEEE Computer Society
This paper first gives a brief interview of AVS, especially on prediction modes of motion estimation by sub-pixel and quarter-pixel interpolation. Furthermore a new sub-pixel interpolation algorithm--EISPI based on analyzing some traditional sub-pixel interpolation algorithms is discussed in details. EISPI mainly adopts the method of threshold decision to divide the ...
Keywords:
Sub pixel, classification, Interpolation, AVS
Keywords:
Sub pixel, classification, Interpolation, AVS
2
July 1997
This paper describes a technique for filter selection. An off-line genetic algorithm search ensures that, for practical applications involving texture processing, only a small number of filters need to be convolved with the image rather than an entire filter bank, hence reducing computation time. The reduced number of filters also ...
Title:
Automatic Selection of Gabor Filters for Pixel Classification
3
September 2008
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 30 Issue 9, September 2008
Publisher: IEEE Computer Society
This paper addresses the problem of visual tracking under very general conditions: a possibly non-rigid target whose appearance may drastically change over time; general camera motion; a 3D scene; and no a priori information except initialization. This is in contrast to the vast majority of trackers which rely on some ...
Keywords:
Pixel classification, Tracking, Motion, Tracking, Motion, Pixel classification
Keywords:
Pixel classification
Tracking, Motion, Pixel classification
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April 2008
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 30 Issue 4, April 2008
Publisher: IEEE Computer Society
A framework for robust foreground detection that works under difficult conditions such as dynamic background and moderately moving camera is presented in this paper. The proposed method includes two main components: coarse scene representation as the union of pixel layers, and foreground detection in video by propagating these layers using ...
Keywords:
Scene Analysis, Scene Analysis, Pixel classification, Pixel classification
Keywords:
Scene Analysis, Pixel classification
Pixel classification
5
March 2018
Soft Computing - A Fusion of Foundations, Methodologies and Applications: Volume 22 Issue 5, March 2018
Publisher: Springer-Verlag
In this paper, we introduce an intra-field deinterlacing algorithm based on a wavelet-content-adaptive back propagation (BP) neural network (BP-NN) using pixel classification. During interpolation, there is an issue of different image features having completely different properties, such as smooth regions, edges, and textures. We use the wavelet transform to divide ...
Keywords:
BP neural network, Deinterlacing, Pixel classification
Full Text:
... based on a wavelet-content-adaptive back propagation (BP)neural network (BP-NN) using pixel classification. . During interpolation, there is an issue of different image ...
Abstract:
... on a wavelet-content-adaptive back propagation (BP) neural network (BP-NN) using pixel classification. . During interpolation, there is an issue of different image ...
Keywords:
Pixel classification
6
January 1982
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 4 Issue 1, January 1982
Publisher: IEEE Computer Society
An image can be segmented by classifying its pixels using local properties as features. Two intuitively useful properties are the gray level of the pixel and the ``busyness,'' or gray level fluctuation, measured in its neighborhood. Busyness values tend to be highly vari-able in busy regions; but great improvements in ...
Keywords:
pixel classification, relaxation, Busyness, segmentation, texture
Keywords:
pixel classification
Title:
Pixel Classification Based on Gray Level and Local ``Busyness''
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November 2012
ACM Transactions on Graphics (TOG): Volume 31 Issue 6, November 2012
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 2, Downloads (12 Months): 25, Downloads (Overall): 463
Full text available:
PDF
Existing video object cutout systems can only deal with limited cases. They usually require detailed user interactions to segment real-life videos, which often suffer from both inseparable statistics (similar appearance between foreground and background) and temporal discontinuities (e.g. large movements, newly-exposed regions following disocclusion or topology change). In this paper, ...
Keywords:
object cutout, pixel classification, video segmentation
Full Text:
... time.CR Categories: I.4.6 [Computer Graphics]: Image Processingand Computer Vision—Segmentation - Pixel classification; ;Keywords: video segmentation, object cutout, pixel classificationLinks: DL PDF WEB ...
... the user interactively (see Section 3.2).These classifiers are integrated for pixel classification, , based onwhich the foreground matte is solved, and the ...
... of the previous methods, our method mainly usescolor statistics for pixel classification, , which inevitably introducessome limitations. Because the local classifier and ...
Keywords:
pixel classification
8
November 2006
Pattern Recognition: Volume 39 Issue 11, November, 2006
Publisher: Elsevier Science Inc.
Pixel-based texture classifiers and segmenters are typically based on the combination of texture feature extraction methods that belong to a single family (e.g., Gabor filters). However, combining texture methods from different families has proven to produce better classification results both quantitatively and qualitatively. Given a set of multiple texture feature ...
Keywords:
Multiple texture methods, Supervised texture classification, Multiple evaluation windows, Texture feature selection
Full Text:
... doi:10.1016/j.patcog.2006.05.016Pattern Recognition 39 (2006) 1996–2009www.elsevier.com/locate/patcogAutomatic texture feature selection for image pixel classi?cation? ?Domenec Puig?, Miguel Angel GarciaIntelligent Robotics and Computer Vision Group, ...
... First IbPRIA, Springer, Berlin, 2003,pp. 793–801.[2] D. Puig, M.A. Garc a, Pixel classi?cation through divergence-basedintegration of texture methods with con?ict resolution, IEEE ICIP,Barcelona, ...
References:
D. Puig, M.A. García, Pixel classification through divergence-based integration of texture methods with conflict resolution, IEEE ICIP, Barcelona, Spain, 2003.
Title:
Automatic texture feature selection for image pixel classification
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January 1990
Pattern Recognition Letters: Volume 11 Issue 1, January 1, 1990
Publisher: Elsevier Science Inc.
Title:
Image pixel classification by chromaticity analysis
10
January 2008
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 30 Issue 1, January 2008
Publisher: IEEE Computer Society
Missing data are common in range images, due to geometric occlusions, limitations in the sensor field of view, poor reflectivity, depth discontinuities, and cast shadows. Using registration to align these data often fails, because points without valid correspondences can be incorrectly matched. This paper presents a maximum likelihood method for ...
Keywords:
Range data, Pixel classification, Maximum Likelihood, Range data, Registration, Maximum Likelihood, Pixel classification, Registration
Keywords:
Pixel classification
Range data, Registration, Maximum Likelihood, Pixel classification
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May 2007
GI '07: Proceedings of Graphics Interface 2007
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 3, Downloads (12 Months): 25, Downloads (Overall): 371
Full text available:
PDF
Modeling 3D objects and scenes is an important part of computer graphics. One approach to modeling is projecting binary patterns onto the scene in order to obtain correspondences and reconstruct a densely sampled 3D model. In such structured light systems, determining whether a pixel is directly illuminated by the projector ...
Keywords:
structured light, 3D reconstruction, direct and global separation
Full Text:
Microsoft Word - gi07.doc Robust Pixel Classification for 3D Modeling with Structured Light Yi Xu Daniel G. ... paper, we introduce a robust, efficient, and easy to implement pixel classification algorithm for this purpose. Our method correctly establishes the lower ... to a captured image yields a simple binary image for pixel classification. . However in practice, the unknown and potentially complex surface ... points: 201528 points vs. 57464 points.......Binary pattern structured light images(a)......Our pixel classification
... robust and accurate classification. In this paper, we present a pixel classification algorithm for structured light systems using binary patterns (Figure 1). ... is illuminated or non-illuminated during structured-light acquisition, and • a pixel classification algorithm which allows structured light systems to work better in ...
... structured-light acquisition and uses the bounds during classification. 3 ROBUST PIXEL CLASSIFICATION ALGORITHM A pixel classification algorithm in binary-pattern structured-light acquisition uses a set of rules ... and Poff for when the pixel is not directly illuminated. Pixel classification methods generally establish the lower and upper bounds of the ...
... Establishing correspondences implies identifying surface points observed by both cameras. Pixel classification produces a set of candidate camera pixels for each projector ...
... objects of diverse materials. To compare the quality of our pixel classification algorithm, we also implemented two standard pixel classification methods for structured light systems. Standard method 1 uses the ...
Abstract:
... paper, we introduce a robust, efficient, and easy to implement pixel classification algorithm for this purpose. Our method correctly establishes the lower ...
Title:
Robust pixel classification for 3D modeling with structured light
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May 2008
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 30 Issue 5, May 2008
Publisher: IEEE Computer Society
This paper presents a quantitative comparison of different algorithms for the removal of stafflines from music images. It contains a survey of previously proposed algorithms and suggests a new skeletonization based approach. We define three different error metrics, compare the algorithms with respect to these metrics and measure their robustness ...
Keywords:
Performance evaluation, Music (Optical Recognition), Pixel classification, Segmentation, Segmentation, Pixel classification, Music (Optical Recognition), Performance evaluation
Keywords:
Pixel classification
Segmentation, Pixel classification, Music (Optical Recognition), Performance evaluation
13
August 2008
IEEE Transactions on Pattern Analysis and Machine Intelligence: Volume 30 Issue 8, August 2008
Publisher: IEEE Computer Society
This paper presents a proposal of a general framework that explicitly models local information and global information in a conditional random field. The proposed method extracts global image features as well as local ones and uses them to predict the scene of the input image. Scene-based top-down information is generated ...
Keywords:
Pixel classification, Markov random fields, Scene Analysis, Markov random fields, Scene Analysis, Pixel classification
Keywords:
Pixel classification, Markov random fields, Scene Analysis
Pixel classification
14
June 2008
ICIAR '08: Proceedings of the 5th international conference on Image Analysis and Recognition
Publisher: Springer-Verlag
The detection of rotten citrus in packing lines is carried out manually under ultraviolet illumination, which is dangerous for workers. Light emitted by the rotten region of the fruit due to the ultraviolet-induced fluorescence is used by the operator to detect the damages. This procedure is required because the low ...
Keywords:
hyperspectral imaging, pixel classification, feature selection, fruit inspection
Abstract:
... segmentation relies on the combination of band selection techniques and pixel classification methods such as classification and regression trees and linear discriminant ...
Keywords:
pixel classification
15
August 2010
ICPR '10: Proceedings of the 2010 20th International Conference on Pattern Recognition
Publisher: IEEE Computer Society
Document Image Binarization techniques have been studied for many years, and many practical binarization techniques have been developed and applied successfully on commercial document analysis systems. However, the current state-of-the-art methods, fail to produce good binarization results for many badly degraded document images. In this paper, we propose a self-training ...
Keywords:
document image binarization, image pixel classification, self-training learning framework
Keywords:
document image binarization, image pixel classification, self-training learning framework
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November 2011
ICTAI '11: Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
Publisher: IEEE Computer Society
In this paper, we propose a new approach for color image simplification in order to improve flame pixel classification. The fire detection performance depends critically on the performance of the flame pixel classifier. Color image simplification is the process of simplifying an image in order to decrease the number of ...
Keywords:
Flame pixel classification, Hierarchical clustering, Minimum Spanning Tree
Abstract:
... approach for color image simplification in order to improve flame pixel classification. . The fire detection performance depends critically on the performance ...
Keywords:
Flame pixel classification, Hierarchical clustering, Minimum Spanning Tree
Title:
A Simple Hierarchical Clustering Method for Improving Flame Pixel Classification
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September 2011
ICDAR '11: Proceedings of the 2011 International Conference on Document Analysis and Recognition
Publisher: IEEE Computer Society
Document image binarization has been studied for decades, and many practical binarization techniques have been proposed for different kinds of document images. However, many state-of-the-art methods are particularly suitable for the document images that suffer from certain specific type of image degradation or have certain specific type of image characteristics. ...
Keywords:
document image binarization, pixel classification, thresholding technique combination
Keywords:
document image binarization, pixel classification, thresholding technique combination
18
January 2018
Neurocomputing: Volume 275 Issue C, January 2018
Publisher: Elsevier Science Publishers B. V.
Using a registration-based coarse segmentation to the pre-processed prostate MRI images to get the potential boundary region.Constructing a prostate pixel classifier in fine segmentation using pre-trained VGG-19 network model.Introducing ensemble learning to the fine segmentation to further improve the segmentation results.Evaluating the proposed method on the PROMIS12 challenge dataset and ...
Keywords:
Deep neural network, MRI prostate segmentation, Ensemble learning, Pixel classification
Keywords:
Pixel classification
19
August 2005
ICML '05: Proceedings of the 22nd international conference on Machine learning
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 0, Downloads (12 Months): 9, Downloads (Overall): 226
Full text available:
Pdf
Online feature selection (OFS) provides an efficient way to sort through a large space of features, particularly in a scenario where the feature space is large and features take a significant amount of memory to store. Image processing operators, and especially combinations of image processing operators, provide a rich space ...
Title:
Online feature selection for pixel classification
20
April 2012
Geoinformatica: Volume 16 Issue 2, April 2012
Publisher: Kluwer Academic Publishers
An important approach for image classification is the clustering of pixels in the spectral domain. Fast detection of different land cover regions or clusters of arbitrarily varying shapes and sizes in satellite images presents a challenging task. In this article, an efficient scalable parallel clustering technique of multi-spectral remote sensing ...
Keywords:
Point-symmetry based distance measure, Remote sensing imagery, Distributed algorithm, Pixel classification, Symmetry detection
Full Text:
... numeric remote sensingdata sets, described in terms of feature vectors.Keywords Pixel classification Distributed algorithm Remote sensing imagery Symmetry detection ... 16:391–4071 IntroductionIn the realm of the remote sensing imagery, the pixel classification of a particularland cover region is often posed as clustering ... properly. Point Symmetry-Based K-Means(Sym) method isused for high-resolution satellite image pixel classification with high-throughputspectral data. Therefore a faster pixel classification method detecting point-symmetry is required to analyze them. Kanungo et ...
... is shown as another thin line stretching between(a)(b) (c)Fig. 3 Pixel classification on SPOT image of Kolkata. (a) Original Kolkata SPOT image ... 11169.933 value, as PKM provides X B =(a)(b) (c)Fig. 4 Pixel classification on I RS image of Mumbai. (a) Original I RS ...
... produce spectral classes.4 ConclusionIn this article, the problem of faster pixel classification of satellite images intodifferent land cover regions is posed as ... feature vector as this is found to be effective in pixel classification [1]in ParSym method, in lieu of intensity values at different ... Int J Remote Sens 26(3):579–5932. Bandyopadhyay S, Pal SK (2001) Pixel classification using variable string genetic algorithms withchromosome differentiation. IEEE Trans Geosci ...
... S (2003) Fuzzy partitioning using a real-coded variable-length geneticalgorithm for pixel classification. . IEEE Trans Geosci Remote Sens 41(5):1075–108120. Mount DM, Arya ...
... also is areviewer of IEEE SMC-C journal.Efficient parallel algorithm for pixel classification in remote sensing imageryAbstractIntroductionClustering using point symmetryKd-tree based nearest neighbor ...
References:
Bandyopadhyay S, Pal SK (2001) Pixel classification using variable string genetic algorithms with chromosome differentiation. IEEE Trans Geosci Remote Sens 39(2):303-308.
Maulik U, Bandyopadhyay S (2003) Fuzzy partitioning using a real-coded variable-length genetic algorithm for pixel classification. IEEE Trans Geosci Remote Sens 41(5):1075-1081.
Keywords:
Pixel classification
Title:
Efficient parallel algorithm for pixel classification in remote sensing imagery
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