Results 21 to 30 of about 429,650 (191)

A TRANSFORMATION METHOD FOR TEXTURE FEATURE DESCRIPTION UNDER DIFFERENT IMAGINE CONDITIONS [PDF]

open access: yesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
For high spatial resolution Remote Sensing images, it is very important to investigate the transformational methods between background and target characteristics.
Z. Guan, J. Yu, T. Feng, A. Li
doaj   +1 more source

Block-based cloud classification with statistical features and distribution of local texture features [PDF]

open access: yesAtmospheric Measurement Techniques, 2015
This work performs cloud classification on all-sky images. To deal with mixed cloud types in one image, we propose performing block division and block-based classification.
H.-Y. Cheng, C.-C. Yu
doaj   +1 more source

A Comparative Study of Two State-of-the-Art Feature Selection Algorithms for Texture-Based Pixel-Labeling Task of Ancient Documents

open access: yesJournal of Imaging, 2018
Recently, texture features have been widely used for historical document image analysis. However, few studies have focused exclusively on feature selection algorithms for historical document image analysis.
Maroua Mehri   +5 more
doaj   +1 more source

Integration of feature distributions for colour texture segmentation [PDF]

open access: yes, 2004
This paper proposes a new framework for colour texture segmentation and determines the contribution of colour and texture. The distributions of colour and texture features provides the discrimination between different colour textured regions in an ...
Ghita, Ovidiu   +2 more
core   +1 more source

Cotton Yield Estimation Based on Vegetation Indices and Texture Features Derived From RGB Image

open access: yesFrontiers in Plant Science, 2022
Yield monitoring is an important parameter to evaluate cotton productivity during cotton harvest. Nondestructive and accurate yield monitoring is of great significance to cotton production.
Yiru Ma   +8 more
doaj   +1 more source

A coal-rock image feature extraction and recognition method

open access: yesGong-kuang zidonghua, 2017
A coal-rock image feature extraction and recognition method based on binary cross-diagonal texture matrix was proposed. Binary cross-diagonal texture matrix of coal-rock image is extracted firstly. Then feature vector of coal-rock image is constructed by
SUN Jiping, YANG Kun
doaj   +1 more source

Evaluating the gray level co-occurrence matrix-based texture features of magnetic resonance images for glioblastoma multiform patients' treatment response assessment

open access: yesJournal of Medical Signals and Sensors, 2023
Background: Medical images of cancer patients are usually evaluated qualitatively by clinical specialists which makes the accuracy of the diagnosis subjective and related to the skills of clinicians.
Sanaz Alibabaei   +4 more
doaj   +1 more source

Feature-aligned shape texturing [PDF]

open access: yesACM SIGGRAPH Asia 2009 papers, 2009
The essence of a 3D shape can often be well captured by its salient feature curves. In this paper, we explore the use of salient curves in synthesizing intuitive, shape-revealing textures on surfaces. Our texture synthesis is guided by two principles: matching the direction of the texture patterns to those of the salient curves, and ...
Kai Xu   +6 more
openaire   +1 more source

Content-Dependent Image Search System for Aggregation of Color, Shape and Texture Features

open access: yesEmitter: International Journal of Engineering Technology, 2019
The existing image search system often faces difficulty to find a appropriate retrieved image corresponding to an image query. The difficulty is commonly caused by that the users’ intention for searching image is different with dominant information of ...
Arvita Agus Kurniasari   +2 more
doaj   +1 more source

Automated classification of childhood brain tumours based on texture feature [PDF]

open access: yesSongklanakarin Journal of Science and Technology (SJST), 2019
We propose a framework for automated classification between normal and abnormal biopsy samples of childhood brain tumour with emphasis on childhood medulloblastoma, a most common childhood brain tumour, using texture features.
Daisy Das   +4 more
doaj   +1 more source

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