Results 231 to 240 of about 125,098 (262)

Construction of texture features

2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009
One well-known and effective method used for computationally efficient texture classification is the use of statistical information on 3×3 pixel blocks such as local binary patterns (LBP). However, there has been negligible research on sizes of pixel blocks beyond 3×3 while using the histogram approach. Specifically, larger or non-square features might
A. Oerlemans, null Qi Zhang, M.S. Lew
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Applications of Texture Features

2019
Texture is a vital visual and the emergent feature for image content explanation. The utilization of object texture is one of the utmost challenging problems in forming effective content-based image retrieval [1].
Jyotismita Chaki, Nilanjan Dey
openaire   +1 more source

Texture Defect Detection Using Invariant Textural Features

2001
In this paper we propose a novel method for the construction of invariant textural features for grey scale images. The textural features are based on an averaging over the 2D Euclidean transformation group with relational kernels. They are invariant against 2D Euclidean motion and strictly increasing grey scale transformations.
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Feature-Based Textures.

2004
This paper introduces feature-based textures, a new image representation that combines features and texture samples for high-quality texture mapping. Features identify boundaries within a texture where samples change discontinuously. They can be extracted from vector graphics representations, or explicity added to raster images to improve sharpness ...
Ganesh Ramanarayanan, Kavita Bala, Bruce Walter   +2 more
openaire   +1 more source

Structural Texture Features

2019
Structural methods depict texture through well-defined primitives and a structure of those primitives’ spatial relationships.
Jyotismita Chaki, Nilanjan Dey
openaire   +1 more source

Pavement texture depth estimation using image-based multiscale features

Automation in Construction, 2022
Zihang Weng, Chenglong Liu, Difei Wu
exaly  

Texture Feature Extraction

2019
This chapter focuses on another image feature called the texture feature. Two types of texture feature methods are discussed: traditional spatial methods and contemporary spectral methods. The chapter first introduces four spatial or handcrafted methods including Tamura, GLCM, MRF, and FD.
openaire   +1 more source

Wheat Fusarium Head Blight Detection Using UAV-Based Spectral and Texture Features in Optimal Window Size

Remote Sensing, 2021
Yingying Dong, Wenjiang Huang, Linyi Liu   +2 more
exaly  

Deep Texture-Aware Features for Camouflaged Object Detection

IEEE Transactions on Circuits and Systems for Video Technology, 2023
Xiaowei Hu, Xuemiao Xu, Yangyang Xu
exaly  

Texture features for browsing and retrieval of image data

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
B S Manjunath
exaly