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Color Edge Detection using the Normalization Anisotropic Gaussian Kernel and Multichannel Fusion
2020
IEEE Access
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Eventually, by incorporating a binarization procedure, a fullfledged framework for color edge detection is developed. ...
In section III, the new edge detector of a normalized scale space for edge detection and multi-space model fusion are presented. ...
doi:10.1109/access.2020.3044341
fatcat:jckehplqpfdkvdclw5no3er2xa
A new approach to edge detection
2002
Pattern Recognition
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This paper introduces the discrete singular convolution (DSC) algorithm for edge detection. ...
Two classes of new edge detectors, DSC edge detector (DSCED) and DSC anti-noise edge detector (DSCANED), are proposed for the detection of multiscale edges. ...
The authors are grateful to the referee for valuable comments and suggestions. ...
doi:10.1016/s0031-3203(01)00147-9
fatcat:z5r5ajlu7bhfzk64srpdjrckzq
Image Tampering Localization Using Demosaicing Patterns and Singular Value Based Prediction Residue
2021
IEEE Access
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As such, we introduce a new algorithm to obtain prediction residue using SVD.
IV. ...
They proposed a new feature measuring the presence of demosaicing artifacts, that is, the logarithm of the geometric mean ratio of the prediction error variance, and introduced a new statistical model ...
The proposed method was compared with existing tampering localization algorithms, the results of which showed that the proposed scheme outperforms state-of-the-art approaches in terms of subjective and ...
doi:10.1109/access.2021.3091161
fatcat:hpaaprqhn5gzbfdolhqxb4mumu
Super Resolution Reconstruction in Mixed Noise Environment
2015
International Journal of Computer Applications
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The fuzzy based impulse noise removal algorithm is along with adaptive sharpening filter based SR using steering kernel regression are used to obtain a HR image. ...
The experimental results confirm the efficacy of the algorithm for different types of images at various noise densities. ...
there are positive values along the edge outline, then the kernel smooths the edge. ...
doi:10.5120/21594-4689
fatcat:diky47xk2zbbpfmz4yv3daqaga
Using Image Processing to Automatically Measure Pearl Oyster Size for Selective Breeding
2019
2019 Digital Image Computing: Techniques and Applications (DICTA)
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The ratio value for this was determined by running the edge detection algorithm over the length of tape exposed in the validation oyster images. ...
The tape measure was planned to be used to calibrate the pixel value to the actual value ratio for the algorithms measurement calculations. ...
doi:10.1109/dicta47822.2019.8945902
dblp:conf/dicta/LapicoSCMKJTJZ19
fatcat:civsc3vkgjhuvccbeazj7mll44
Incremental episodic segmentation and imitative learning of humanoid robot through self-exploration
2016
Neurocomputing
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Imitation learning through self-exploration is an essential mechanism in developing sensorimotor skills for human infants as well for robots. ...
We assume that a primitive sense of self is the prerequisite for successful social interaction rather than an outcome of it. ...
They used a general change point detection algorithm called Robust Singular Spectrum Transform (RSST) [11] and solves the segmentation problem by finding the boundaries of motifs. ...
doi:10.1016/j.neucom.2015.09.021
fatcat:iu2kgxl4hjegbnqcakrz5y2ngu
Edges, transitions and criticality
2014
Pattern Recognition
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We study the framework of reconstructible systems in a microcanonical formulation, show how it redefines edge completion, and how it can be used to evaluate and assess quantitatively the adequation of ...
edges as candidates for compact representations. ...
Acknowledgment
Suman Kumar Maji's PhD is funded by a CORDIS grant and Région Aquitaine OPTAD research project grant. ...
doi:10.1016/j.patcog.2013.12.013
fatcat:vfzs2jthv5a2nc32ezfqbdznlq
A survey of methods for time series change point detection
2016
Knowledge and Information Systems
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Detection of change points is useful in modelling and prediction of time series and is found in application areas such as medical condition monitoring, climate change detection, speech and image analysis ...
Finally, we present some grand challenges for the community to consider. ...
They then use a test statistic based upon the kernel Fisher discriminant ratio as a measure of homogeneity between windows. ...
doi:10.1007/s10115-016-0987-z
pmid:28603327
pmcid:PMC5464762
fatcat:qtjvqsgdkjgwtivwlmjn27xyde
Edge Detection Enhancement Based on Filtering and Threshold Estimation
2020
International Journal of Engineering and Advanced Technology
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An edge detection is a critical tool under image processing and computer vision. ...
Entropy, Mean Squares Error, and Peak Signal to Noise Ratio values were examined and it gave better results. ...
of Engineering and Advanced Technology (IJEAT) ISSN: 2249 -8958, Volume-9 Issue-5, June 2020 Acknowledgements: The authors would like to thank Imam Saud Islamic University college of Computer Science for ...
doi:10.35940/ijeat.e9957.069520
fatcat:nitoo3opi5fglclf5p73fmcn4i
Edge detection using nonlinear structure tensor
2022
Nonlinear Engineering
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In order to improve the performance of edge detection for noisy images, a new edge detection method based on nonlinear structure tensor is proposed. ...
Therefore, this method is more suitable for edge detection of noisy images, and the performance of this method is better than that of the comparison method and can improve the performance of edge detection ...
[6] proposed a system based on a singular value feature vector, and the gradient operator edge detection algorithm. ...
doi:10.1515/nleng-2022-0038
fatcat:cd25mv34uvaslmawsmiv3gthxu
Multi-scale crest line extraction based on half Gaussian Kernels
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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In this paper we propose a new ridge/valley detection method in images based on the difference of rotating Gaussian semi filters adapted in a multi-scale process. ...
Crest line extraction has always been a challenging task in image processing and its applications. It is possible to detect ridges and valleys in images using second order filters. ...
(CIRAD) for providing the enabling environment and financial resources that allowed us to achieve this work. ...
doi:10.1109/icassp.2014.6854575
dblp:conf/icassp/MagnierABMJ14
fatcat:gflfjlhgdjdb7dnp5gjfpacqdm
Breast Microcalcification Detection Algorithm Based on Contourlet and ASVM
2019
Algorithms
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The algorithm overcomes various difficulties in microcalcification detection and has great clinical application value. ...
The present study proposes an algorithm for detecting microcalcification on mammography for early breast cancer. ...
Acknowledgments: Thanks to my family for their support. Thanks to my teachers and classmates for giving me guidance on my studies.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/a12070135
fatcat:l432vgkcrjba5jwfz7qodjb4iq
A novel image segmentation algorithm for clinical CT images using wavelet transform, curvelet transform and multiple kernel FCM
2015
Applied Mathematical Sciences
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Multiple Kernel Fuzzy C-means (MKFCM) algorithm is used for segmentation purpose of the image. ...
A combined approach of different techniques such as Wavelet, Curvelet and Multiple Kernel Fuzzy C-Means algorithm was carry out in this paper. ...
Fuzzy cmeans clustering algorithm is used for spherical clusters only. Multiple kernel fuzzy c-means algorithm is a new extension to the FCM. ...
doi:10.12988/ams.2015.53216
fatcat:f33w2cj2hbegtl2x737euyt2me
Unsharp masking using quadratic filter for the enhancement of fingerprints in noisy background
2013
Pattern Recognition
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The paper summarizes the design and implementation of a quadratic edge detection filter based on Volterra series. ...
The filter is employed in an unsharp masking scheme for enhancing fingerprints in a dark and noisy background. ...
The principal issue in employing a quadratic filter is the identification of its kernel H 2 . Powell optimization [28] is used for obtaining H 2 as this algorithm has a fast rate of convergence. ...
doi:10.1016/j.patcog.2013.05.014
fatcat:ovajoo7t25gmnhn3skem4ucnq4
Research on LSSVM-based License Plate Character Recognition
2018
JCBPSC
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This paper proposes a new method of License plate (LP) character recognition based on least square support vector machine (LSSVM) and singular value decomposition (SVD). ...
The compressed singular value feature vector is used to present the features of each LP image. Then uses LSSVM to train these features and to recognition. Experiment is based on LP image. ...
Fig. 5 : 5 Result of edge detection.
Fig. 6 : 6 Result of using laplace enhancement algorithm.
Fig. 7 : 7 Segmentation result of LP character. ...
doi:10.24214/jcbps.c.8.4.43341
fatcat:lvwhcadg65ho3ipexmbg5hszaq
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