Petersen graph multi-orientation based multi-scale ternary pattern (PGMO-MSTP): an efficient descriptor for texture and material recognition

I El Khadiri, Y El Merabet, AS Tarawneh… - … on Image Processing, 2021 - ieeexplore.ieee.org
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …
被引用次数：13 相关文章

[引用][C] Petersen Graph Multi-Orientation based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

KI El, MY El, AS Tarawneh, Y Ruichek… - IEEE TRANSACTIONS …, 2021 - eprints.sztaki.hu
Petersen Graph Multi-Orientation based Multi-Scale Ternary Pattern (PGMO-MSTP): An
Efficient Descriptor for Texture and Material Recognition - SZTAKI Publication Repository …
[PDF] researchgate.net

[PDF][PDF] Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

I El Khadiri, Y El Merabet, AS Tarawneh, Y Ruichek… - structure (OSLGS) - researchgate.net
Classifying and modeling texture images, especially 1 those with significant rotation,
illumination, scale, and view-2 point variations, is a hot topic in the computer vision field. 3 …

Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition.

IE Khadiri, YE Merabet, AS Tarawneh… - IEEE Transactions on …, 2021 - europepmc.org
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …

Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

IE Khadiri, YE Merabet, AS Tarawneh… - IEEE Transactions on …, 2021 - dl.acm.org
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …

Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

I El Khadiri, Y El Merabet… - … : a publication of …, 2021 - pubmed.ncbi.nlm.nih.gov
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …

[引用][C] Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

IE Khadiri, YE Merabet, AS Tarawneh… - IEEE Transactions …, 2021 - ui.adsabs.harvard.edu
Petersen Graph Multi-Orientation Based Multi-Scale Ternary Pattern (PGMO-MSTP): An
Efficient Descriptor for Texture and Material Recognition - NASA/ADS Now on home page ads …

[引用][C] Petersen Graph Multi-Orientation based Multi-Scale Ternary Pattern (PGMO-MSTP): An Efficient Descriptor for Texture and Material Recognition

KI El, MY El, AS Tarawneh, Y Ruichek… - IEEE TRANSACTIONS …, 2021 - eprints.sztaki.hu
Petersen Graph Multi-Orientation based Multi-Scale Ternary Pattern (PGMO-MSTP): An
Efficient Descriptor for Texture and Material Recognition - SZTAKI Publication Repository …