Version 1
: Received: 15 December 2020 / Approved: 18 December 2020 / Online: 18 December 2020 (16:21:50 CET)
How to cite:
K. Ardestani, S. Combination of Texture, Color and Shape Operators to Describe Image Content: A Survey. Preprints2020, 2020120479. https://doi.org/10.20944/preprints202012.0479.v1
K. Ardestani, S. Combination of Texture, Color and Shape Operators to Describe Image Content: A Survey. Preprints 2020, 2020120479. https://doi.org/10.20944/preprints202012.0479.v1
K. Ardestani, S. Combination of Texture, Color and Shape Operators to Describe Image Content: A Survey. Preprints2020, 2020120479. https://doi.org/10.20944/preprints202012.0479.v1
APA Style
K. Ardestani, S. (2020). Combination of Texture, Color and Shape Operators to Describe Image Content: A Survey. Preprints. https://doi.org/10.20944/preprints202012.0479.v1
Chicago/Turabian Style
K. Ardestani, S. 2020 "Combination of Texture, Color and Shape Operators to Describe Image Content: A Survey" Preprints. https://doi.org/10.20944/preprints202012.0479.v1
Abstract
In many image processing and computer vision applications, the main aim is to describe image contents. So, different visual properties such as color, texture and shape are extracted to make aim. In this respect, texture information play important role in image description and visual pattern classification. Texture is referred to a specific local distribution of intensities that is repeated throughout the image. Since now different operations or descriptors have been proposed to analysis texture characteristics. In the multi object images specific texture operators usually doesn’t provide accurate results. So, in many cases, combination of texture operators are used to achieve more discriminant features. In this paper, some combination methods are survived to analysis effect of combinational texture features in image content description. Also, in the result part, different related methods are compared in terms of accuracy and computational complexity.
Computer Science and Mathematics, Algebra and Number Theory
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
