Advances in Image Analysis: Shapes, Textures and Multifractals
A special issue of Journal of Imaging (ISSN 2313-433X).
Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 13157
Special Issue Editor
Special Issue Information
Dear Colleagues,
Shape and texture play very important roles in characterising image features in the fields of computer vision, image analysis and machine learning. Various types of shape descriptors, such as image moments, area, circularity, convexity and major axis orientation, are commonly used for quantifying shape information. Popular texture features used in applications involving segmentation and classification are Grey Level Dependence/Co-Occurrence/Run-Length Matrices and Local Binary/Ternary/Quinary Patterns.
Multifractal features are now increasingly being used in biomedical imaging and machine learning applications. Traditional generalizations of fractal systems based on a range of singularity exponents and multifractal spectra have now found their way into the domain of image analysis as techniques for representing intensity (or color) variations around pixel neighborhoods. The singularity spectrum of intensity variations in an image has been shown to contain highly useful information related to both the shape and texture characteristics needed for the effective identification and classification of regions of interest. Several new multifractal analysis methods have been recently reported in the field of medical image processing. These include algorithms for microcalcification detection in mammograms, analysis of tissue structures in histopathological images, nuclei segmentation in whole slide images, emphysema classification in CT images, feature enhancement in ultrasound videos and mammographic breast density estimation.
This Special Issue aims to promote further research into all aspects of shape/texture analysis and applications of multifractal measures and descriptors. We welcome original contributions showing the effectiveness of shape, texture and multifractal features in image segmentation, feature analysis, shape analysis, image classification and biomarker discovery.
Prof. Dr. Ramakrishnan Mukundan
Guest Editor
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Keywords
- image texture descriptors
- texture feature extraction
- multifractal analysis
- singularity spectrum
- tissue image analysis
- image classification
- region of interest segmentation
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