期刊文献+

基于GPU的CLABP特征提取方法研究

Research on color local angel binary patterns texture feature extraction method based on GPU
下载PDF
导出
摘要 彩色局部角度二值模式(CLABP)可以有效地提取彩色图像中的纹理特征,但是算法复杂、计算量大。针对这一问题,采用GPU实现CLABP特征提取和表示的并行方法。该方法一方面使用异步处理的方式实现CLABP的并行加速,另一方面采用共享内存的形式减少读取数据的次数。为了验证该方法的有效性,在Outex纹理图像数据库上与CPU程序性能进行对比,结果表明,GPU实现方法可以提升加速比约25倍。 Color local angel binary patterns (CLABP)method can extract color texture feature effectively. But the algorithm is complex and has large amount of calculation. In order to solve the problem, this paper proposes a GPU implement for color local angel binary patterns texture feature extraction and presentation. On one hand, this method use asynchronous processing way to realize CLABP parallel acceleration. On the other hand, it also improves the implement via shared memory to reduce the number of reading data. In order to verify the validity of proposed method, we compare our method with CPU implement on Outex texture dataset. The experiment results demonstrate that the acceleration rate can achieve 25 times.
作者 罗沛 梁鹏
出处 《微型机与应用》 2014年第16期37-39,共3页 Microcomputer & Its Applications
关键词 GPU 彩色局部角度二值模式 异步处理 GPU color local angel binary pattern(CLABP) asynchronous processing
  • 相关文献

参考文献9

  • 1AHONEN T, HADID A, PIETIKAINEN M. Face description with local binary pattern: application to face recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(12):2037-2041. 被引量:1
  • 2OJALA T, PIETIKAINEN M, MAENPAA T. Muhiresolution gray-scale and rotation-invariant texture classification with local binary patterns[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7):971-987. 被引量:1
  • 3林似水,郑力新.联合LBP与SOM的多分辨率织物疵点检测[J].微型机与应用,2012,31(23):45-47. 被引量:4
  • 4郭春凤,何建农.彩色与纹理不变性的阴影消除新算法[J].微型机与应用,2013,32(5):38-41. 被引量:3
  • 5LEE S H, CHOI J Y, ROY M, et al. Local color vector binary patterns from multi-channel face images for face recognition[J]. IEEE Transactions on Image Processing, 2012, 21 (4) :2347-2353. 被引量:1
  • 6KIRKDB,HWUWW.大规模并行处理器编程实战[M].陈曙晖,熊淑华,译.北京:清华大学出版社.2010. 被引量:7
  • 7Sanders J,Kandrot E.GPU高性能编程CUDA实战[M].聂雪军,译.北京:机械工业出版社,2011. 被引量:10
  • 8张舒,禇艳利主编..GPU高性能运算之CUDA[M],2009:276.
  • 9OJALA T, MAENPAA T, PIETIKAINEN M, et al. Outex-a new framework for empirical evaluation of texture analysis algorithms[C]. Proceedings of the 16th Conference on Pattern Recognition, 2002:701-706. 被引量:1

二级参考文献18

  • 1周家香,朱建军,张红亚.基于C1C2C3彩色不变特征的阴影检测与辐射恢复研究[J].工程勘察,2007,35(6):52-54. 被引量:5
  • 2BISSI L, BARUFFA G, PLACIDI P, et al. Patch based yam defect detection using Gabor filters [C]. I2MIC, 2012 IEEE International, 2012: 240-244. 被引量:1
  • 3PRIYA S, KUMAR T A, PAUL D V. A novel approach to fabric defect detection using digital image processing [C].ICSCCN, 2011: 228-232. 被引量:1
  • 4Ding S, Liu Z, Li C. AdaBoost learning for fabric defect detection based on HOG and SVM [C]. International Conference on Multimedia Technology, 2011:2903-2906. 被引量:1
  • 5Guan S, Yuan J, Ma K. Fabric defect detection based on wavelet reconstruction[C]. ICMT 2011, 2011:3520-3523. 被引量:1
  • 6Zhang L, He Xh, Zhang Hb. A fabric defects detection method using SAR imaging [C]. 2010 6th International Conference on WiCOM, 2010:1-4. 被引量:1
  • 7Jia X. Fabric defect detection based on open source computer vision library OpenCV[C]. 2010 2nd International Conference on ICSPS, 2010:342-345. 被引量:1
  • 8Zhang YH, Yuen CWM, Wong WK. A new intelligent fabric defect detection and classification system based on gabor filter and modified elman neural network[C]. ICACC,2010:652-656. 被引量:1
  • 9BRADSKI G, KAEBLER A. Learning OpenCV [M].南京:东南大学出版社.2009. 被引量:1
  • 10郝灿,朱信忠,赵建民,徐慧英.基于改进型LBP特征的运动阴影去除算法[J].计算机系统应用,2010,19(5):80-83. 被引量:7

共引文献19

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部