场景文本检测是场景文本识别中重要的一步,也是一个具有挑战性的问题。不同于一般的目标检测,场景文本检测的主要挑战在于自然场景图像中的文本具有任意方向,小的尺寸,以及多种宽高比。论文在TextBoxes[8]的基础上进行改进,提出了一个...场景文本检测是场景文本识别中重要的一步,也是一个具有挑战性的问题。不同于一般的目标检测,场景文本检测的主要挑战在于自然场景图像中的文本具有任意方向,小的尺寸,以及多种宽高比。论文在TextBoxes[8]的基础上进行改进,提出了一个适用于任意方向文本的检测器,命名为OSTD(Oriented Scene Text Detector),可以有效且准确地检测自然场景中任意方向的文本。论文在公共数据集上对提出OSTD的进行评估。所有实验结果都表明,无论在准确性,还是实时性方面OSTD都是极具竞争力的方法。在1024×1024的ICDAR2015 Incidental Text数据集[16]上,OSTD的F-Measure=0.794,FPS=10.7。展开更多
Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.T...Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.展开更多
文摘场景文本检测是场景文本识别中重要的一步,也是一个具有挑战性的问题。不同于一般的目标检测,场景文本检测的主要挑战在于自然场景图像中的文本具有任意方向,小的尺寸,以及多种宽高比。论文在TextBoxes[8]的基础上进行改进,提出了一个适用于任意方向文本的检测器,命名为OSTD(Oriented Scene Text Detector),可以有效且准确地检测自然场景中任意方向的文本。论文在公共数据集上对提出OSTD的进行评估。所有实验结果都表明,无论在准确性,还是实时性方面OSTD都是极具竞争力的方法。在1024×1024的ICDAR2015 Incidental Text数据集[16]上,OSTD的F-Measure=0.794,FPS=10.7。
基金supported by the National Natural Science Foundation of China(No.61170106)
文摘Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.
