...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Real-Time Image Processing >Fast Gabor texture feature extraction with separable filters using GPU
【24h】

Fast Gabor texture feature extraction with separable filters using GPU

机译：使用GPU使用可分离的滤镜快速提取Gabor纹理特征

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Gabor wavelet transform is one of the most effective texture feature extraction techniques and has resulted in many successful practical applications. However, real-time applications cannot benefit from this technique because of the high computational cost arising from the large number of small-sized convolutions which require over 10 min to process an image of 256 x 256 pixels on a dual core CPU. As the computation in Gabor filtering is parallelizable, it is possible and beneficial to accelerate the feature extraction process using GPU. Conventionally, this can be achieved simply by accelerating the 2D convolution directly, or by expediting the CPU-efficient FFT-based 2D convolution. Indeed, the latter approach, when implemented with small-sized Gabor filters, cannot fully exploit the parallel computation power of GPU due to the architecture of graphics hardware. This paper proposes a novel approach tailored for GPU acceleration of the texture feature extraction algorithm by using separable 1D Gabor filters to approximate the non-separable Gabor filter kernels. Experimental results show that the approach improves the timing performance significantly with minimal error introduced. The method is specifically designed and optimized for computing unified device architecture and is able to achieve a speed of 16 fps on modest graphics hardware for an image of 256(2) pixels and a filter kernel of 32(2) pixels. It is potentially applicable for real-time applications in areas such as motion tracking and medical image analysis.
机译：Gabor小波变换是最有效的纹理特征提取技术之一，并已在许多成功的实际应用中得到了应用。但是，由于大量的小尺寸卷积需要花费10分钟以上的时间才能在双核CPU上处理256 x 256像素的图像，因此实时计算应用无法从该技术中受益。由于Gabor滤波中的计算是可并行化的，因此有可能并有利于使用GPU加速特征提取过程。传统上，这可以通过直接加速2D卷积或通过加速基于CPU的高效FFT的2D卷积来实现。确实，后一种方法在使用小型Gabor滤波器实现时，由于图形硬件的体系结构而无法充分利用GPU的并行计算能力。本文提出了一种新颖的方法，该方法通过使用可分离的一维Gabor滤波器来近似不可分离的Gabor滤波器内核，为GPU加速纹理特征提取算法量身定制。实验结果表明，该方法显着提高了定时性能，并引入了最小的误差。该方法经过专门设计和优化，用于计算统一的设备体系结构，并且能够在适度的图形硬件上针对256（2）像素的图像和32（2）像素的过滤器内核实现16 fps的速度。它可能适用于运动跟踪和医学图像分析等领域的实时应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号