Spectral edit distance method for image clustering
作者： Nian Wang , Jun Tang , Jiang Zhang , Yi-Zheng Fan , Dong Liang
DOI: 10.1007/978-3-540-72524-4_37
关键词: Adjacency list 、 Spectral graph theory 、 Line graph 、 Adjacency matrix 、 Artificial intelligence 、 Pattern recognition 、 Laplacian matrix 、 Computer science 、 Distance matrix 、 Graph energy 、 Incidence matrix
摘要: The spectral graph theories have been widely used in the domain of image clustering where editing distances between graphs are critical. This paper presents a method for edit distance constructed on images. Using feature points each image, we define weighted adjacency matrix relational and obtain covariance based spectra all graphs. Then project vectorized spectrum to eigenspace matrix, derive pairwise We also conduct some theoretical analyses support our method. Experiments both synthetic data real-world images demonstrate effectiveness approach.
springer.com
acm.org 
sci-hub.st 参考文章(10)
Miguel Angel Lozano, Francisco Escolano, ACM attributed graph clustering for learning classes of images Lecture Notes in Computer Science. pp. 247- 258 ,(2003) , 10.1007/3-540-45028-9_22
Graph-Based Representations in Pattern Recognition Lecture Notes in Computer Science. ,vol. 5534, ,(1998) , 10.1007/978-3-642-20844-7
Horst Bunke, P. Foggia, C. Guidobaldi, M. Vento, Graph clustering using the weighted minimum common supergraph Lecture Notes in Computer Science. pp. 235- 246 ,(2003) , 10.1007/3-540-45028-9_21
Andrew D. Bagdanov, Marcel Worring, First Order Gaussian Graphs for Efficient Structure Classification Pattern Recognition. ,vol. 36, pp. 1311- 1324 ,(2003) , 10.1016/S0031-3203(02)00227-3
Soo Beom Park, Jae Won Lee, Sang Kyoon Kim, Content-based image classification using a neural network Pattern Recognition Letters. ,vol. 25, pp. 287- 300 ,(2004) , 10.1016/J.PATREC.2003.10.015
S. Belongie, J. Malik, J. Puzicha, Shape matching and object recognition using shape contexts IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 24, pp. 509- 522 ,(2002) , 10.1109/34.993558
D Guillamet, J Vitrià, B Schiele, Introducing a weighted non-negative matrix factorization for image classification Pattern Recognition Letters. ,vol. 24, pp. 2447- 2454 ,(2003) , 10.1016/S0167-8655(03)00089-8
Huaijun Qiu, Edwin R. Hancock, Graph matching and clustering using spectral partitions Pattern Recognition. ,vol. 39, pp. 22- 34 ,(2006) , 10.1016/J.PATCOG.2005.06.014
Bin Luo, Richard C. Wilson, Edwin R. Hancock, A spectral approach to learning structural variations in graphs Pattern Recognition. ,vol. 39, pp. 1188- 1198 ,(2006) , 10.1016/J.PATCOG.2006.01.001
Giorgio Giacinto, Fabio Roli, Lorenzo Bruzzone, Combination of neural and statistical algorithms for supervised classification of remote-sensing images Pattern Recognition Letters. ,vol. 21, pp. 385- 397 ,(2000) , 10.1016/S0167-8655(00)00006-4