Results 31 to 40 of about 140,951 (296)

DTNLS: 3D Point Cloud Segmentation Based on 2D Image and 3D Point Cloud Double Texture Feature

IEEE Access
Panoramic segmentation of 3D point clouds is an essential and challenging technology for robots with 3D detection and measurement capabilities. In order to fuse the color information of 2D image pixels with the spatial position information of the 3D ...
Zhiguang Liu, Xiaoxiao Yan, Jiahui Zhao, Yong Shi, Fei Yu, Jian Zhao   +5 more
doaj   +1 more source

Unsupervised texture segmentation [PDF]

, 1998
A novel unsupervised multispectral texture segmentation algorithm is introduced. The textured image segmentation is based on a causal adaptive regression model prediction for detecting different types of texture segments which are present at the image. Texture segments are detected in four mutually perpendicular directions in the image lattice.
openaire   +1 more source

Segmentation precedes face categorization under suboptimal conditions

Frontiers in Psychology, 2015
Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and
Carlijn eVan Den Boomen, Carlijn eVan Den Boomen, Johannes Jacobus Fahrenfort, Johannes Jacobus Fahrenfort, Tineke M. Snijders, Tineke M. Snijders, Tineke M. Snijders, Tineke M. Snijders, Chantal eKemner, Chantal eKemner, Chantal eKemner   +10 more
doaj   +1 more source

Multi texture analysis of colorectal cancer continuum using multispectral imagery [PDF]

, 2016
Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images.
Bouridane, Ahmed, Chaddad, Ahmad, Desrosiers, Christian, Hassan, Lama, Tanougast, Camel, Toews, Matthew   +5 more
core   +4 more sources

Unsupervised Segmentation Of Texture Images [PDF]

SPIE Proceedings, 1988
Past work on unsupervised segmentation of a texture image has been based on several restrictive assumptions to reduce the difficulty of this challenging segmentation task. Typically, a fixed number of different texture regions is assumed and each region is assumed to be generated by a simple model.
MICHEL X., LEONARDI, Riccardo, GERSHO A.
openaire   +1 more source

Neutrosophic Set Transformation Matrix Factorization Based Active Contours for Color Texture Segmentation

IEEE Access, 2019
Active contour model (ACM) has widely used for segmenting two-phase images. However, its performance may not be satisfactory for some color texture images when their features cannot be effectively extracted.
Yongsheng Dong, Hongyan Zhang, Zhonghua Liu, Chunlei Yang, Guo-Sen Xie, Lintao Zheng, Lin Wang   +6 more
doaj   +1 more source

A Texture Integrated Deep Neural Network for Semantic Segmentation of Urban Meshes

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
3-D geo-information is essential for many urban related applications. Point cloud and mesh are two common representations of the 3-D urban surface. Compared to point cloud data, mesh possesses indispensable advantages, such as high-resolution image ...
Yetao Yang, Rongkui Tang, Mengjiao Xia, Chen Zhang   +3 more
doaj   +1 more source

Model-based learning of local image features for unsupervised texture segmentation

, 2017
Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task.
Kiechle, Martin, Kleinsteuber, Martin, Storath, Martin, Weinmann, Andreas   +3 more
core   +1 more source

Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters [PDF]

, 2012
In this paper, local distributions of low order Gaussian Markov Random Field (GMRF) model parameters are proposed as texture features for unsupervised texture segmentation.Instead of using model parameters as texture features, we exploit the variations ...
Bennett, Michael, Dharmagunawardhana, Chathurika, Mahesan, Niranjan, Mahmoodi, Sasan   +3 more
core   +1 more source

Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters [PDF]

, 2014
Segmentation of an object from a video is a challenging task in multimedia applications. Depending on the application, automatic or interactive methods are desired; however, regardless of the application type, efficient computation of video object ...
Alatan, A. Aydin, Sener, Ozan, Ugur, Kemal   +2 more
core   +2 more sources