Results 21 to 30 of about 38,722 (268)
Multi-Phase Image Segmentation Based on Low-Rank Prior Decomposition
IEEE Access, 2022 Natural images generally contain both structure component and texture component. The existing image segmentation models based on piecewise smooth cannot handle such natural images containing texture well.
Jianlou Xu, Yuying Guo, Leigang Huo
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Unsupervised Texture Segmentation: Comparison of Texture Features [PDF]
Mehran University Research Journal of Engineering and Technology, 2010 Texture is an important image-content that has been utilized for different machine intelligent tasks, like those in machine vision and remote sensing, which identify objects of interest by segmenting the image texture.
AHSAN AHMAD URSANI +2 more
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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.
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Texture Segmentation using LBP embedded Region Competition
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2005 In this paper, we modify the region competition method to segment textures. First, local Binary pattern (LBP) histogram is adopted to capture the texture information.
Qing Xu, Jie Yang, Siyi Ding
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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.
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Transductive Segmentation of Textured Meshes [PDF]
, 2010 This paper addresses the problem of segmenting a textured mesh into objects or object classes, consistently with user-supplied seeds. We view this task as transductive learning and use the flexibility of kernel-based weights to incorporate a various number of diverse features.
Chauve, Anne-Laure +3 more
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DTNLS: 3D Point Cloud Segmentation Based on 2D Image and 3D Point Cloud Double Texture Feature
IEEE AccessPanoramic 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 +5 more
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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 +3 more
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Texture recognition system based on the Deep Neural Network [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2020 This paper presents a deep learning-based image texture recognition system. The methodology taken in this solution is formed in a bottom-up manner. It means we swipe a moving window through the image in order to categorize if a given region belongs to ...
R. Kapela
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Frame representations for texture segmentation
IEEE Transactions on Image Processing, 1996 We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and 2-D envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zero crossings.
Laine, Andrew F., Fan, Jian
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