文件名称:OTSU_BMPtoBIN
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- 上传时间:2015-10-15
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文件大小:394.71kb
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大律法(OTSU)灰度图像阈值提取算法(C语言实现)。文件中已经有已经编译好的可执行文件,可以批量把灰度图片转化成二值化的二进制图像文件,可用于LCD显示屏视频动画的开发(例如Badapple)。
阀值是图像二值化处理中非常重要的一个参数,意思就是:如果灰度图像的像素颜色值大于该阀值就把该点当作黑色,小于该阀值就把改点当作白色。最简单的做法就是把阀值取为127(255的一半),但是这种做法是不科学的,处理后的二值化图像效果也很不理想。关于阀值的选取是一门很深的学问,有很多经典的算法用于选取该阀值,理论我就不做过多描述了,感兴趣的自己趣网络上搜索相关资料,我这里采用的是比较经典的大律法(OTSU)。-Large law (OTSU) threshold grayscale image extraction algorithm (C language). File has been compiled executable file, you can bulk of the gray image is converted to binary binary image file that can be used for the LCD display video animation development (for example Badapple).
Image binarization threshold is a very important process parameters, means: If the pixel color values gray image is larger than the threshold to put the point as a black, less than the threshold put the change point as white. The easiest way is to take the threshold of 127 (255 in half), but this approach is unscientific, binary image post-processing effects also far ideal. Select on the threshold of a very deep knowledge, there are many classical algorithms for selecting the threshold theory I do not do too much descr iption, and search for relevant information of interest to their own interest on the network, I used here It is more classic big law (OTSU).
阀值是图像二值化处理中非常重要的一个参数,意思就是:如果灰度图像的像素颜色值大于该阀值就把该点当作黑色,小于该阀值就把改点当作白色。最简单的做法就是把阀值取为127(255的一半),但是这种做法是不科学的,处理后的二值化图像效果也很不理想。关于阀值的选取是一门很深的学问,有很多经典的算法用于选取该阀值,理论我就不做过多描述了,感兴趣的自己趣网络上搜索相关资料,我这里采用的是比较经典的大律法(OTSU)。-Large law (OTSU) threshold grayscale image extraction algorithm (C language). File has been compiled executable file, you can bulk of the gray image is converted to binary binary image file that can be used for the LCD display video animation development (for example Badapple).
Image binarization threshold is a very important process parameters, means: If the pixel color values gray image is larger than the threshold to put the point as a black, less than the threshold put the change point as white. The easiest way is to take the threshold of 127 (255 in half), but this approach is unscientific, binary image post-processing effects also far ideal. Select on the threshold of a very deep knowledge, there are many classical algorithms for selecting the threshold theory I do not do too much descr iption, and search for relevant information of interest to their own interest on the network, I used here It is more classic big law (OTSU).
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下载文件列表
00000.bmp
badapple.dev
badapple.layout
EasyBMP/
EasyBMP/BSD_(revised)_license.txt
EasyBMP/EasyBMP.cpp
EasyBMP/EasyBMP.h
EasyBMP/EasyBMP.o
EasyBMP/EasyBMP_BMP.h
EasyBMP/EasyBMP_ChangeLog.txt
EasyBMP/EasyBMP_DataStructures.h
EasyBMP/EasyBMP_VariousBMPutilities.h
LCDͼƬȡģ_v20150603.exe
main.cpp
main.o
Makefile.win
output.h
badapple.dev
badapple.layout
EasyBMP/
EasyBMP/BSD_(revised)_license.txt
EasyBMP/EasyBMP.cpp
EasyBMP/EasyBMP.h
EasyBMP/EasyBMP.o
EasyBMP/EasyBMP_BMP.h
EasyBMP/EasyBMP_ChangeLog.txt
EasyBMP/EasyBMP_DataStructures.h
EasyBMP/EasyBMP_VariousBMPutilities.h
LCDͼƬȡģ_v20150603.exe
main.cpp
main.o
Makefile.win
output.h
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