Supporting Data and Code: Fast clustering in linear independent 1D subspaces: segmentation of multi-channel images with high spatial resolution

Kopriva, Ivica; Brbić, Maria; Tolić, Dijana; Antulov Fantulin, Nino; Chen, Xinjian (2016) Supporting Data and Code: Fast clustering in linear independent 1D subspaces: segmentation of multi-channel images with high spatial resolution. [Dataset] (Submitted)

	Archive (TGZ) (Supporting Data and Code v3) - research data Download (1MB)
	Archive (TGZ) (Supporting Data and Code v3) - Submitted Version - research data Download (1MB)

Abstract

Algorithms for subspace clustering (SC) such as sparse and low- rank representation SC are effective in terms of the accuracy but suffer from high computational complexity. We propose algorithm for SC of (highly) similar data points drawn from union of linear independent one-dimensional subspaces with computational complexity that is linear in number of data points. The algorithm finds a dictionary that represents data in reproducible kernel Hilbert space (RKHS). Afterwards, data are projected into RKHS by using empirical kernel map (EKM). Segmentation into subspaces is realized by applying the max operator on projected data. We provide rigorous proof that for noise free data proposed approach yields exact clustering into subspaces. We also prove that EKM-based projection yields less correlated data points. Due to nonlinear projection, the proposed method can adopt to linearly nonseparable data points. We demonstrate accuracy and computational efficiency of the proposed algorithm on synthetic dataset as well as on segmentation of tissue components from image of unstained specimen in histopathology.

Item Type:	Dataset
Additional Information:	The supporting data and code in Matlab for "Fast Clustering in Linear Independent 1D Subspaces: Segmentation of Multi-Channel Images With High Spatial Resolution".
Uncontrolled Keywords:	subspace clustering; linear independent 1D subspaces; empirical kernel map; image segmentation; unstained specimen
Subjects:	NATURAL SCIENCES > Mathematics > Applied Mathematics and Mathematical Modeling TECHNICAL SCIENCES TECHNICAL SCIENCES > Computing > Data Processing
Divisions:	Division of Electronics
Projects:	Project title Project leader Project code Project type Analiza nelinearnih komponenata s primjenama u kemometriji i patologiji Ivica Kopriva IS-9.01/232 HRZZ Bilateral Chinese-Croatian Project UNSPECIFIED UNSPECIFIED bilaterala
Depositing User:	Dijana Tolić
Date Deposited:	29 Apr 2016 12:10
URI:	http://fulir.irb.hr/id/eprint/2761

Available Versions of this Item

• Supporting Data and Code: Fast clustering in linear independent 1D subspaces: segmentation of multi-channel images with high spatial resolution (deposited 20 Jan 2016 15:29)
  • Supporting Data and Code: Fast clustering in linear independent 1D subspaces: segmentation of multi-channel images with high spatial resolution (deposited 03 Feb 2016 14:11)
    • Supporting Data and Code: Fast clustering in linear independent 1D subspaces: segmentation of multi-channel images with high spatial resolution (deposited 29 Apr 2016 12:10) [Currently Displayed]

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