Image segmentation based on pixel feature manifold

Haopeng Zhang; Zhiguo Jiang

doi:10.1117/12.902145

8 December 2011 Image segmentation based on pixel feature manifold

Haopeng Zhang, Zhiguo Jiang

Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 800307 (2011) https://doi.org/10.1117/12.902145
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Image segmentation is an important problem in pattern recognition, computer vision and other related area, which is still a research focus. In this paper, we consider the segmentation as pixel classification scheme and introduce a manifold way to address this problem. Some local features, such as Haar, LBP and SIFT, are used to represent each pixel in the image together with the basic property of the pixel. We put these pixel features on a manifold called pixel feature manifold (PFM) obtained via manifold learning methods and classify pixels with k-NN classifier in the pixel embedding space. Experimental results on MSRC image dataset show that our PFM method can effectively segment images.

Citation Download Citation

Haopeng Zhang and Zhiguo Jiang "Image segmentation based on pixel feature manifold", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 800307 (8 December 2011); https://doi.org/10.1117/12.902145

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available