Type-2 fuzzy thresholding using GLSC histogram of human visual nonlinearity characteristics.

Image thresholding is one of the most important approaches for image segmentation and it has been extensively used in many image processing or computer vision applications. In this paper, a new image thresholding method is presented using type-2 fuzzy sets based on GLSC histogram of human visual nonlinearity characteristics (HVNC).The traditional GLSC histogram takes the image spatial information into account in a different way from two-dimensional histogram. This work refines the GLSC histogram by embedding HVNC into GLSC histogram. To select threshold based on the redefined GLSC histogram, we employ the type-2 fuzzy set, whose membership function integrates the effect of pixel gray value and local spatial information to membership value. The type-2 fuzzy set is subsequently transformed into a type-1 fuzzy set for fuzziness measure computation via type reduction. Finally, the optimal threshold is obtained by minimizing the fuzziness of the type-1 fuzzy set after an exhaustive search. The experiment on different types of images demonstrates the effectiveness and the robustness of our proposed thresholding technique.

• Publication year

  2011

• Venue

  Optics Express

• Publication date

  2011-05-23

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1364/OE.19.010656PMID 21643321
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Type-2 Fuzzy Sets as Functions on Spaces

  2010cited by this paper
• New entropic thresholding approach using gray-level spatial correlation histogram

  2010cited by this paper
• Comment on: "Image thresholding using type II fuzzy sets". Importance of this method

  2010cited by this paper
• Automatic Histogram Threshold Using Fuzzy Measures

  2010cited by this paper
• Uncertainty measures for general type-2 fuzzy sets

  2009cited by this paper
• Comment on: "Image thresholding using type II fuzzy sets"

  2008cited by this paper
• Entropic thresholding based on gray-level spatial correlation histogram

  2008cited by this paper
• Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint]

  2007cited by this paper
• Image thresholding using restricted equivalence functions and maximizing the measures of similarity

  2007cited by this paper
• Advances in type-2 fuzzy sets and systems

  2007cited by this paper
• Uncertainty measures for interval type-2 fuzzy sets

  2007cited by this paper
• Type-2 fuzzy sets and systems: an overview

  2007cited by this paper
• Image segmentation based on fuzzy connectedness using dynamic weights

  2006cited by this paper
• Image thresholding using two-dimensional Tsallis-Havrda-Charvát entropy

  2006cited by this paper
• Image thresholding using type II fuzzy sets

  2005cited by this paper
• Survey over image thresholding techniques and quantitative performance evaluation

  2004cited by this paper
• A thresholding method based on two-dimensional Renyi's entropy

  2004cited by this paper
• Image Thresholding by Maximizing the Index of Nonfuzziness of the 2-D Grayscale Histogram

  2002cited by this paper
• Image segmentation by histogram thresholding using fuzzy sets

  2002cited by this paper
• Type-2 fuzzy sets made simple

  2002cited by this paper
• Analysis of fuzzy thresholding schemes

  2000cited by this paper
• Image thresholding using fuzzy entropies

  1998cited by this paper
• Investigations on fuzzy thresholding based on fuzzy clustering

  1997cited by this paper
• Fuzzy sets

  1996cited by this paper
• Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets

  1996cited by this paper
• Image thresholding by minimizing the measures of fuzzines

  1995cited by this paper
• Thresholding of digital images using two-dimensional entropies

  1992cited by this paper
• Fuzzy thresholding: mathematical framework, bound functions and weighted moving average technique

  1990cited by this paper
• Automatic thresholding of gray-level pictures using two-dimensional entropy

  1989cited by this paper
• Image enhancement and thresholding by optimization of fuzzy compactness

  1988cited by this paper
• A survey of thresholding techniques

  1988cited by this paper
• A new method for gray-level picture thresholding using the entropy of the histogram

  1985cited by this paper
• An Analytical Derivation of Visual Nonlinearity

  1980cited by this paper
• ON THE MEASURE OF FUZZINESS AND NEGATION Part I: Membership in the Unit Interval

  1979cited by this paper
• A Threshold Selection Method from Gray-Level Histograms

  1979cited by this paper
• A survey of threshold selection techniques

  1978cited by this paper
• The concept of a linguistic variable and its application to approximate reasoning - I

  1975cited by this paper

• NE-MTOC Formation in Skeletal Muscle Is Mbnl2-Dependent and Occurs in a Sequential and Gradual Manner

  2025cites this paper
• ATG8-dependent LMX1B-autophagy crosstalk shapes human midbrain dopaminergic neuronal resilience

  2023cites this paper
• Introduction to Image Segmentation and Clustering

  2021cites this paper
• An maize leaf segmentation algorithm based on image repairing technology

  2020cites this paper
• Firefly optimization-based segmentation technique to analyse medical images of breast cancer

  2020cites this paper
• LIR-dependent LMX1A/LMX1B autophagy crosstalk shapes human midbrain dopaminergic neuronal resilience

  2019cites this paper
• Chapter 2 Body Movement Analysis and Recognition

  2019cites this paper
• A contextualized approach for segmentation of foliage in different crop species

  2019cites this paper
• Environmentally adaptive crop extraction for agricultural automation using super-pixel and LAB Gaussian model

  2018cites this paper
• Image Thresholding Segmentation Based on Two Dimensional Histogram Using Gray Level and Local Entropy Information

  2018cites this paper
• DeepCotton: in-field cotton segmentation using deep fully convolutional network

  2017cites this paper
• A New Type-2 Fuzzy Algorithm for Unmanned Aerial Vehicle Image Segmentation

  2017cites this paper
• Body Movement Analysis and Recognition

  2016cites this paper
• An Image-Based Approach to Automatic Crop Organ Extraction via Low-Rank Matrix Recovery

  2016cites this paper
• Region-based colour modelling for joint crop and maize tassel segmentation

  2016cites this paper
• Leg Ulcer Wound Image Analysis of Sickle cell Anemia- a fuzzy thresholding based Approach

  2016cites this paper
• A survey of image processing techniques for plant extraction and segmentation in the field

  2016cites this paper
• Fine-grained maize tassel trait characterization with multi-view representations

  2015cites this paper
• Field crop extraction robust to illumination variations based on specularity learning

  2015cites this paper
• Joint crop and tassel segmentation in the wild

  2015cites this paper
• Entropic image thresholding based on GLGM histogram

  2014cites this paper
• Image segmentation using modified SLIC and Nyström based spectral clustering

  2014cites this paper
• Automatic image-based detection technology for two critical growth stages of maize: Emergence and three-leaf stage

  2013cites this paper
• A New Method for Gray Level Image Thresholding Using Spatial Correlation Features and Ultrafuzzy Measure

  2013cites this paper
• TYPE-II FUZZY ENTROPIC THRESHOLDING USING GLSC HISTOGRAM BASED ON PROBABILITY PARTITION

  2013cites this paper
• INVESTIGATIONS ON ENTROPY BASED THRESHOLD METHODS

  2013cites this paper
• Crop segmentation from images by morphology modeling in the CIE L*a*b* color space

  2013cites this paper
• An automatic detection method to the field wheat based on image processing

  2013cites this paper
• Specularity-invariant crop extraction with probabilistic super-pixel Markov random field

  2013cites this paper
• A Modified Gray level Co-occurrence Matrix based Thresholding for Object Background Classification

  2012cites this paper
• Automatic Image Segmentation using Ultra Fuzziness

  2012cites this paper
• Unsupervised Image Thresholding using Fuzzy Measures

  2011cites this paper