Degradation adaptive texture classification [PDF]
2014 IEEE International Conference on Image Processing (ICIP), 2014 Image degradations such as noise, blur and scale-variations are known to significantly affect the classification process of textured images. However, due to difficult visual according conditions, such degradation are often prevalent in digital real-world images.
Michael Gadermayr, Andreas Uhl
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Active learning strategies for robotic tactile texture recognition tasks
Frontiers in Robotics and AIAccurate texture classification empowers robots to improve their perception and comprehension of the environment, enabling informed decision-making and appropriate responses to diverse materials and surfaces.
Shemonto Das +2 more
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FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification
Sensors, 2012 This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness.
Wei-Hao Lee +2 more
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A Completed Multi-Scale Local Statistics Pattern for Texture Classification
Image Analysis and StereologyBinary pattern methods play a vital role in extracting texture features. However, most of existing methods struggle to capture comprehensive and discriminative texture information.
Xiaochun Xu, Bin Li, Q.M. Jonathan Wu
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SuroTex: Surrounding texture datasetMendeley Data
Data in BriefTexture analysis can be considered as one of the most important topics in the field of image processing and computer vision. However, the existing texture datasets such as KTH-TIPS, KTH-TIPS2, USPTex, DTD, and ALOT still have limitations which causes the
Muhammad Ardi Putra +2 more
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Audio Classification from Time-Frequency Texture
, 2008 Time-frequency representations of audio signals often resemble texture images. This paper derives a simple audio classification algorithm based on treating sound spectrograms as texture images.
Slotine, Jean-Jacques, Yu, Guoshen
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Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks [PDF]
, 2018 Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs).
Abbas, Alhabib +3 more
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EFFECTIVE MULTI-RESOLUTION TRANSFORM IDENTIFICATION FOR CHARACTERIZATION AND CLASSIFICATION OF TEXTURE GROUPS [PDF]
ICTACT Journal on Image and Video Processing, 2011 Texture classification is important in applications of computer image analysis for characterization or classification of images based on local spatial variations of intensity or color.
S. Arivazhagan +2 more
doaj
Extracting Terrain Texture Features for Landform Classification Using Wavelet Decomposition
ISPRS International Journal of Geo-Information, 2021 Accurate landform classification is a crucial component of geomorphology. Although extensive classification efforts have been exerted based on the terrain factor, the scale analysis to describe the macro and micro landform features still needs standard ...
Yuexue Xu +4 more
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Multi-resolution texture classification based on local image orientation [PDF]
, 2008 The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image ...
A. Guérin-Dugué +13 more
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