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Using a Fuzzy Object-Relational Database for Colour Image Retrieval
[chapter]
2006
Lecture Notes in Computer Science
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The paper presents a fuzzy database management system, and a fuzzy method for dominant colour description of images, on which an image retrieval system is built. ...
The paper shows the suitability of the fuzzy database management system for this kind of applications when the images are characterized by fuzzy data. ...
In this paper we use a novel method for describing images based on its dominant colours [1] . This method takes advantage of fuzzy set theory for dealing with vagueness in colour descriptions. ...
doi:10.1007/11766254_26
fatcat:eeysha54zrga7bcjmd6lqzuhm4
Interval type-2 Beta Fuzzy Near set based approach to content based image retrieval
[article]
2018
arXiv
pre-print
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In this article, we introduce a new category of beta type-2 fuzzy sets for the description of image characteristics as well as the near sets approach for image recovery. ...
near and fuzzy sets approaches. ...
In other words, tolerance near sets are used as a fundament for a qualitative method to evaluate the resemblance between the items without the need for these items description. ...
arXiv:1812.07098v1
fatcat:byabp7j4kbf3na4ktdripvtowe
A novel fusion approach to content-based image retrieval
2005
Pattern Recognition
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This paper proposes a novel fusion approach to content-based image retrieval. ...
As a result, the resemblance of two images is measured by an overall similarity fusing both region-based and global/semi-global-based image level similarities. ...
Consider two fuzzy sets C u ( x) and C v ( x) for different regions u and v in images A and B, let f u and f v be the corresponding fuzzy centers with the assumption of f u f v . ...
doi:10.1016/j.patcog.2005.04.005
fatcat:vkyql47gtbbxhbwgh2djkjptna
Rough Sets and Near Sets in Medical Imaging: A Review
2009
IEEE Transactions on Information Technology in Biomedicine
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In addition, a brief introduction to near sets and near images with an application to MRI images is given. ...
Near sets offer a generalization of traditional rough set theory and a new approach to classifying perceptual objects by means of features in solving medical imaging problems. ...
For example, imprecision in a segmented image can be represented and analyzed using fuzzy sets. ...
doi:10.1109/titb.2009.2017017
pmid:19304490
fatcat:2yzka5fe3rg5xn7z5iqtk7zulu
Toward a Better Integration of Spatial Relations in Learning with Graphical Models
[chapter]
2010
Studies in Computational Intelligence
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The method is based on graph kernels, in order to derive a metrics for comparing images. ...
The main contribution of the paper is situated in highlighting the challenges that follow in terms of image representation, if fuzzy models are considered for estimating relation satisfiability. ...
the usefulness of fuzzy spatial information for image representation. ...
doi:10.1007/978-3-642-00580-0_5
fatcat:qswotjiakzarrd5kq5kjtxavoq
Computational intelligence for multimedia and industrial applications
2017
Multimedia tools and applications
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Computational intelligence approaches such as neural network, particle swarm optimization, evolutionary algorithm, fuzzy set, and rough sets are adopted in many multimedia and industrial applications, ...
like visual based quality control, image enhancement in consumer electronics, video based recognition of identity or behaviors, audio based speech recognition for enhanced human like interaction with machines ...
Acknowledgments We would like to express our appreciation to all the authors for their informative contributions and the reviewers for their support and constructive critiques in making this special issue ...
doi:10.1007/s11042-017-5154-3
fatcat:b5mr3ghvijgdrol723guqp7lay
Controlled Triangularization Fingerprint Verification Inscribed in a Rhombus Using Fuzzy Feature Matching
2014
International Journal of Computer and Electrical Engineering
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This paper proposes a novel method, a Fuzzy Feature Match (FFM) based on a controlled triangle feature set inscribed in a rhombus to match the deformed fingerprints. ...
The fingerprint is represented by the fuzzy feature set. The fuzzy features set similarity is used to analyze the similarity among fingerprints. ...
The similarity between the fuzzy feature set was used to characterize the similarity between fingerprints. A fuzzy similarity measure for two triangles was first introduced. ...
doi:10.7763/ijcee.2014.v6.807
fatcat:kjxlp6db6zdebjf3jyytoso7fm
An Algorithm for Distorted Fingerprint Matching Based on Local Triangle Feature Set
2006
IEEE Transactions on Information Forensics and Security
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This paper proposes a novel method, a fuzzy feature match (FFM) based on a local triangle feature set to match the deformed fingerprints. ...
The FFM method maps the similarity vector pair to a normalized value which quantifies the overall image to image similarity. ...
Liu for revising the paper. ...
doi:10.1109/tifs.2006.873605
fatcat:fuz4dei5nnd3xgb5svilcaxlyi
Computational Intelligence in Multimedia Processing: Foundation and Trends
[chapter]
2008
Studies in Computational Intelligence
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In addition, a very brief introduction to near sets and near images which offer a generalization of traditional rough set theory and a new approach to classifying perceptual objects by means of features ...
This chapter presents a broad overview of Computational Intelligence (CI) techniques including Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough ...
This section is limited to a very brief introduction to near sets and near images useful in image pattern recognition. ...
doi:10.1007/978-3-540-76827-2_1
fatcat:7jl4ir66vvcl7g436ektwkqwpy
Image Segmentation Using Mean Shift Based Fuzzy C-Means Clustering Algorithm: A Novel Approach
2015
International Journal of Multimedia and Ubiquitous Engineering
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Based on the 5 set of images of the simulation results show that this algorithm combines the advantages of the mean shift algorithm and FCM algorithm, the improved algorithm in segmentation processing ...
Initially, image segmentation into many small homogeneous area using the mean shift algorithm is conducted, segmentation and uniform area, rather than pixels as the new node. ...
Using mean shift algorithm for image pre segmentation, to the pre segmentation of homogeneous regions obtained as a FCM cluster sample set. ...
doi:10.14257/ijmue.2015.10.5.39
fatcat:7aw2ntihergd5kpzl4dwfpntqu
A Fuzzy Logic Approach to Identifying Brain Structures in MRI Using Expert Anatomic Knowledge
1999
Computers and Biomedical Research
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We report a novel computer method for automatic labeling of structures in 3D MRI data sets using expert anatomical knowledge that is coded in fuzzy sets and fuzzy rules. ...
This labeling process simulates the iterative process that we ourselves use to locate structures in images. ...
Sheppard for generous assistance. Some images were supplied by Dr. Harvey S. Levin, University of Maryland. Phillip Berryhill and Dr. ...
doi:10.1006/cbmr.1999.1516
pmid:10587468
fatcat:porksru3indktjv7q2ecxiec4u
Spatial data mining on remote sensing perspective
2016
International Journal of Latest Trends in Engineering and Technology
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Fuzzy set based clustering can generate near realistic clusters than the hard clustering algorithms. ...
Cosine similarity was used for calculating the resemblance between two spatial-temporal models. ...
doi:10.21172/1.74.036
fatcat:mdrfpf5gefg7lojxpmknvcloym
FACE RECOGNITION IN EIGEN DOMAIN WITH NEURO-FUZZY CLASSIFIER AND EVOLUTIONARY OPTIMIZATION
2012
International Journal of Image Processing and Vision Science
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It consists of two stages: Eigenface approach is used for feature extraction and genetic algorithm based feed forward Neuro-Fuzzy System is used for face recognition. ...
Classification of face images to a particular class is done using an artificial neural network. ...
It resembles human deciding with its power to work from near data and discovered accurate solutions. Fuzzy logic deals with logical thinking that is abstract thought rather than fixed and exact. ...
doi:10.47893/ijipvs.2012.1024
fatcat:2bzne7hsb5bhjpzuqblbimn4xm
A Survey Of The State-Of-The-Arts On Neutrosophic Sets In Biomedical Diagnoses
2017
Zenodo
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Fuzzy techniques have extensive solutions for the medical domain applications; however incorporating a new neutrosophic approaches in the medical domain proves its superiority. ...
In real world applications, soft computing is an inspirational domain for encoding imprecision and uncertainty. ...
[27] proposed a novel method for image de-noising based on neutrosophic set approach. Three membership sets T, I and F in the NS set were used to describe an image G. ...
doi:10.5281/zenodo.1412521
fatcat:wexcss4jcvembeuxhu2ipbyxyu
Change detection of land use and land cover in an urban region with SPOT-5 images and partial Lanczos extreme learning machine
2010
Journal of Applied Remote Sensing
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This paper presents a new image classification approach based on a novel neural computing technique that is applied to identify the LULC patterns in a fast growing urban region with the aid of 2.5-meter ...
Improved land management capacity is critically dependent on real-time or near real-time monitoring of land-use/land cover change (LUCC) to the extent to which solutions to a whole host of urban/rural ...
Most fuzzy logic methods are hybrid methods, for example, the fuzzy c-means (FCM) algorithm [15] is a hybrid between fuzzy logic and the statistical algorithm (e.g., c-means). ...
doi:10.1117/1.3518096
fatcat:3y7yswgr45eehmhns5kbku2uae
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