Open Access
Texture Segmentation via Scattering Transform
Huajuan Wu,Ming-Jun Li,Ming-Xin Zhang,Jinlong Zheng,Jian Shen +4 more
- 01 Jan 2013
4
TL;DR: Experimental results indicate that high accuracy can be achieved for both texture segmentation and license plate location with the proposed methods.
read more
Abstract: Texture contains high and low frequency information which could be hierarchically extracted by scattering the texture along multiple paths, with a cascade of wavelet modulus operators implemented in a deep convolutional network, which builds a scattering energy distribution network. Therefore, the scattering transform is used, in this paper, to get texture energy features. Besides, the classification of scattering energy feature matrix at all levels is done by using the Ostu global threshold processing method. Experimental results indicate that high accuracy can be achieved for both texture segmentation and license plate location with the proposed methods.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A Precision-Recall Criterion Based Consensus Model For Fusing Multiple Segmentations
TL;DR: A hierarchical and efficient way to optimize the consensus energy function related to this fusion model that exploits a simple and deterministic iterative relaxation strategy combining the different segments or individual regions belonging to the segmentation ensemble in the final solution is proposed.
16
A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem
Lazhar Khelifi,Max Mignotte +1 more
TL;DR: This paper presents a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments.
14
•Journal Article
Classification of hyperspectral images using scattering transform
PS Ashitha,Sowmya,K P Soman +2 more
TL;DR: A new method for the classification of the hyperspectral images in which the translational and rotational invariance features of each pixel in the image is extracted by applying the scattering transform to the image.
Textured image segmentation via scattering transform and score fusion
Chaimae Anibou,Mohammed Nabil Saidi,Driss Aboutajdine +2 more
- 01 Jan 2016
TL;DR: This paper integrated information fusion on score level to combine the scores obtained by SVM classifier during classification process, using probability theory, to obtain a more accurate result of segmentation.
References
Convolutional networks and applications in vision
Yann LeCun,Koray Kavukcuoglu,Clement Farabet +2 more
- 03 Aug 2010
TL;DR: New unsupervised learning algorithms, and new non-linear stages that allow ConvNets to be trained with very few labeled samples are described, including one for visual object recognition and vision navigation for off-road mobile robots.
Invariant Scattering Convolution Networks
Joan Bruna,Stéphane Mallat +1 more
TL;DR: The mathematical analysis of wavelet scattering networks explains important properties of deep convolution networks for classification.
Group Invariant Scattering
TL;DR: This paper constructs translation-invariant operators on L 2 .R d /, which are Lipschitz-continuous to the action of diffeomorphisms, and extendsScattering operators are extended on L2 .G/, where G is a compact Lie group, and are invariant under theaction of G.
•Posted Content
Invariant Scattering Convolution Networks
Joan Bruna,Stéphane Mallat +1 more
TL;DR: A wavelet scattering network as discussed by the authors computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification, cascading wavelet transform convolutions with nonlinear modulus and averaging operators.
630
A hybrid license plate extraction method based on edge statistics and morphology
Bai Hongliang,Liu Chang-ping +1 more
- 23 Aug 2004
TL;DR: This work presents a hybrid license plate extraction algorithm based on the edge statistics and morphology for monitoring the highway ticketing systems and can quickly and correctly detect the region of vehicle license plates.
312