文件名称:Edge-Thinning
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Windows] [Visual C] [Basic/ASP] [源码]
- 上传时间：
- 2016-09-13
- 文件大小：
- 118kb
- 下载次数：
- 0次
- 提 供 者：
- moha****
- 相关连接：
- 无
- 下载说明：
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Gray Level Edge Thinning Method
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
-Gray Level Edge Thinning Method
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
-Gray Level Edge Thinning Method
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
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下载文件列表
EdgeThin.frm
EdgeThin.log
EdgeThin1.Vbp
EdgeThin1.vbw
LENA.IMG
MSSCCPRJ.SCC
PIC1.IMG
steg1.log
aj11.img