I am extracting the features like mean,variance,kurtosis,etc for images in a database.Here after extracting the features for an single whether normalization has to be done or after extracting the features for all the images normalization has to done

Question

Nithya SIvasamy 2015-10-26

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/251021-i-am-extracting-the-features-like-mean-variance-kurtosis-etc-for-images-in-a-database-here-after-ext

回答： Image Analyst 2015-10-26

I am extracting the features from the database images.

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Image Analyst 2015-10-26

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/251021-i-am-extracting-the-features-like-mean-variance-kurtosis-etc-for-images-in-a-database-here-after-ext#answer_197344

If you are doing automated classification, it's recommended you normalize your feature numbers. Let's say you have two feature classes that have values around 1 and 3, and another feature class that has values around a million. If you do automated classification, it might think that there are only two classes because the first two are so close together that they look like a single class when comparing it to a class that has values of a million. But if you can normalize them all so that they all have values around 0-1, then it will probably recognize that there are 3 distinct classes.