How many ways are generally used for image segmentation using only Image processing?

I want to segment an image using image processing (without using machine learning). How many ways are used for segmentation? genrally I used color based segmentation using thresholding.

Is there any other ways?

[Akira Agata]

Please take a look at "Image Segmentation" section of the Documentation. There should be a lot of hint !

Image Segmentation

[K M Ibrahim Khalilullah]

@Akira Agata Thanks for your comments. I used Matlab a lot, but I did not think like you.

Thanks it helps me a lot.

Answer 1

[KALYAN ACHARJYA]

Yes, the approach of image segmentation depends on type of input image and complexity associated with the ROI and back ground objects. In disctinct RGB image, you can use color based segmentation.

For other you can create a mask and apply the mask on input image, approaches are thresholding (multiple ways, global, local), distance transform, very popular Otshu's methd (Thresholding), watershed, edge detection etc and followed by morphological operation (if required)

Some cases you get the very good results, if you apply contrast enahancement (Histogram Equalization) before apply the segmnetaion method, there after only proceed to subsequents work.

Highly Recomended: Please refer Gonalez Book of Image Segmnetaion Chapter to get the foundation.

Hope it Helps!

[K M Ibrahim Khalilullah]

Thanks for comments. Gonzalez books or other books are not always enough for real applications.

[KALYAN ACHARJYA]

I have mentioned Gonzalez Book (specifically-Not Others), this book is synonyms of Introduction to Digital Image Processing. It gives the soilid foundation, which would be great help for real applications.

How many ways are used for segmentation?

There are no specific numbers, the fundametal approaches, I have already mentioned.

[K M Ibrahim Khalilullah]

Would you give some example using edge detection based and histogram equlization based segmentation, please?