Hi! I'm facing a problem of not being able to predict which cluster contains the image i require in a k-means clustering method. I've enclosed the details of the problem.

2 次查看（过去 30 天）
Meera Girijan
Meera Girijan 2016-4-28
编辑： Meera Girijan 2016-4-30
I'm doing an image segmentation using k-means algorithm to extract just a particular feature from a whole image, for instance a car from the surrounding environment. I've taken three clusters for this. I need to save just the cluster that contains the car, but not able to isolate it since the clusters are generated randomly.
  3 个评论
显示 1更早的评论
Meera Girijan
Meera Girijan 2016-4-28
编辑：Meera Girijan 2016-4-28
@jgg Based on the color and its intensities in the image each component gets separated.Image detection is what i wanted, but this also gave me a desired output. In the image attached below you can see the car separated from the surroundings in cluster 1.
Meera Girijan
Meera Girijan 2016-4-28
@jgg if you could suggest some other efficient method for image detection it would be helpful too. I need to model this separated image.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Walter Roberson
Walter Roberson 2016-4-28
You cannot use k-means clustering alone to detect the presence or absence of something. k-means clustering is going to find the given number of clusters without having any interpretation of what the clusters mean. If you feed it an image of a banana instead of an image of a car, it is going to find 3 clusters in the image of the banana.
You should therefore be extracting feature descriptions from portions of the image and run clustering on the feature descriptions -- possibly only on two clusters ("matches" and "does not match") You can then given an interpretation to the clustering based upon knowing what the features imply.
  4 个评论
显示 2更早的评论
Meera Girijan
Meera Girijan 2016-4-30
编辑：Meera Girijan 2016-4-30
@image analyst Hi!Just wanted to get some more information. Part of my project requires capturing a 2D real time image and extracting a car alone from it without any of the background details. I read up on CBIR and found a lot about image detection. I tried using SURF implementation also. I was getting the interested points, but retrieving the image back seems to be a challenge.The input image for our project will be dynamic and will keep changing every time so I am not able to fix a contour line even if I try to calculate the interested points based on that. I have attached the output i get from kmeans clustering based on colour. The only short coming is that this works only when there's a clear distinguishing color combination . car6 is the actual image and car6sample1 is the output. that is how i want the output to be even when there is no distinct color difference.Could you help me out with this?

请先登录，再进行评论。

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Color Segmentation 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by