SEEDS-Based Superpixel Segmentation Method With Texture Fusion

CHEN Chang; LIU Yong-jian; XIE Qing

Chinese

您当前的位置：

首页 >

文章列表页 >

SEEDS-Based Superpixel Segmentation Method With Texture Fusion

更新时间：2026-09-04

- SEEDS-Based Superpixel Segmentation Method With Texture Fusion
- Vol. 35, Issue 3, Pages: 64-67(2018)
- 作者机构：
  
  武汉理工大学计算机科学与技术学院,湖北,武汉,470070
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
移动端阅览
陈畅, 刘永坚, 解庆. 融合纹理特征的SEEDS超像素分割算法[J]. 微电子学与计算机, 2018, 35(3): 64-67, 73.

CHEN Chang, LIU Yong-jian, XIE Qing. SEEDS-Based Superpixel Segmentation Method With Texture Fusion[J]. 2018, 35(3): 64-67.
陈畅, 刘永坚, 解庆. 融合纹理特征的SEEDS超像素分割算法[J]. 微电子学与计算机, 2018, 35(3): 64-67, 73. DOI：

CHEN Chang, LIU Yong-jian, XIE Qing. SEEDS-Based Superpixel Segmentation Method With Texture Fusion[J]. 2018, 35(3): 64-67. DOI：

摘要

在SEEDS算法的基础上

进行了改进

提出了T-SEEDS算法.其通过融合纹理信息

来增强图像分割的效果

并较好的解决了超像素个数较小的情况下

SEEDS算法分割效率不高的问题.

Abstract

This article introduces an improved algorithm based on SEEDS

T-SEEDS. T-SEEDS algorithm enhances the efficiency of image segmentation by add texture information into the algorithm

which solves the problem nicely that SEEDS cant segment effectively with small number of superpixel at the same time.

关键词

Keywords

references

Van den Bergh M, Boix X, Roig G, et al. SEEDS: superpixels extracted via energy-driven sampling[J]. International Journal of Computer Vision, 2012, 111(3): 298-314. DOI: 298

Veksler O, Boykov Y, Mehrani P. Superpixels and supervoxels in an energy optimization framework[C]// Computer Vision ECCV 2010, European Conference on Computer Vision, Heraklion, Crete, Greece, September 5-11, 2010, Proceedings. DBLP, 2010: 211-224.

Ren X F, Malik J. Learning a classification model for segmentation[C]//9th IEEE International Conference on Computer Vision. France, 2003: 10-17.

Shi J, Malik J. Normalized cuts and image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(8): 888-905. DOI: 888

Boix X, Roig G, Leistner C, et al. Nested Sparse Quantization for Efficient Feature Coding[C]// European Conference on Computer Vision. Springer-Verlag, 2012: 744-758.

Moore A P, Prince S J D, Warrell J, et al. Superpixel lattices[C]//Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008: 1-8.

Comaniciu D, Meer P. Mean shift: a robust approach toward fea-ture space analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24 (5): 603-619. DOI: 603

Levinshtein A, Stere A, Kutulakos K N, et al. TurboPixels: fast superpixels using geometric flows[J]. IEEE Transactions on Pattern Analysis % Machine Intelligence, 2009, 31(12): 2290-2297. DOI: 2290

Achanta R, Shaji A, Smith K, et al. Slic superpixels[R]. Lau-sanne, Vaud, Switzerland: Swiss federal Institute of Technology, 2010.

宋熙煜, 周利莉, 李中国, 等. 图像分割中的超像素方法研究综述[J]. 中国图像图形学报, 2015, 20(5): 599-608. DOI: 599

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Implementation and verification of a dual-chain power gating strategy for low power design

Design of ultra-low power real-time clock circuits

A review of large model development: technological evolution from BERT to Deepseek

High gain stability high temperature operational amplifier based on reverse body bias

Monte carlo analysis of V-layout trench SiC neutron detector

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰