Following the ever-growing sizes of image databases, effective methods for visualising such databases and navigating through them are much sought after. These methods should provide an “overview” of a complete database together with the possibility to zoom into certain areas during a specific search. It is crucial that the user interacts in an intuitive way with such a system in order to effectively arrive at images of interest. In this chapter, we look at several techniques that have been presented in the literature and allow for browsing and navigation of large image databases.
Principal Component Analysis (Pca)
Principal component analysis transforms a number of high dimensional correlated variables into a smaller number of uncorrelated variables called principal components and allows to reduce the dimensionality whilst preserving the “essence” of the data. High dimensional data is normally vast in size and ungraspable by the human mind, making some form of representation necessary.
In order to calculate the principal components, the mean vector of the data (which also defines the first principal component) is calculated and subtracted from the samples (hence, resulting in a distribution centred around the origin). Using singular value decomposition (SVD), the remaining components are obtained by producing a diagonal matrix with eigenvalues in descending order. Each singular value is proportional to the square root of the variances and the corresponding eigenvectors are the principal components. Once these have been calculated, all samples (i.e., images) in the database can be projected onto the principal components and the projection weights be used for assigning coordinates for the display of each image thumbnail (i.e., for the display in a two-dimensional space, such as a monitor the first two principal components would be used).
Key Terms in this Chapter
Multidimensional Scaling (MDS): A dimensionality reduction technique used for projecting high-dimensional data into a low-dimensional space in an optimal way that introduces as little distortion to the original data as possible.
Query-by-Example Retrieval: Retrieval paradigm in which a query is provided by the user and the system retrieves instances similar to the query.
Principal Component Analysis (PCA): An orthogonal linear transform used to transform data into a new coordinate system which maximises the variance captured by the first few base vectors (the principal components).
Image Database Navigation: The browsing of a complete image collection based, for example, on CBIR concepts.
Content-Based Image Retrieval (CBIR): Retrieval of images based not on keywords or annotations, but based on features extracted directly from the image data.
Complete Chapter List
Detailed Table of Contents
Yin-Leng Theng, Schubert Foo, Dion Goh, Jin-Cheon Na
Leonardo Candela, Donatella Castelli, Pasquale Pagano
Mohammed Nasser Al-Suqri, Esther O.A. Fatuyi
Jian-hua Yeh, Shun-hong Sie, Chao-chen Chen
Juan C. Lavariega, Lorena G. Gomez, Martha Sordia-Salinas, David A. Garza-Salazar
George Pyrounakis, Mara Nikolaidou
Ian H. Witten, David Bainbridge
Yin-Leng Theng, Nyein Chan Lwin Lwin, Jin-Cheon Na, Schubert Foo, Dion Hoe-Lian Goh
Schubert Foo, Yin-Leng Theng, Dion Hoe-Lian Goh, Jin-Cheon Na
Fu Lee Wang, Christopher C. Yang
K. S. Chudamani, H. C. Nagarathna
Payam M. Barnaghi, Wei Wang, Jayan C. Kurian
Giovanni Semeraro, Pierpaolo Basile, Marco de Gemmis, Pasquale Lops
Shiyan Ou, Christopher S.G. Khoo, Dion Hoe-Lian Goh
Wooil Kim, John H.L. Hansen
Irene Lourdi, Mara Nikolaidou
Neide Santos, Fernanda C.A. Campos, Regina M.M. Braga Villela
Svenja Hagenhoff, Björn Ortelbach, Lutz Seidenfaden
Stefano Paolozzi, Fernando Ferri, Patrizia Grifoni
Ana Kovacevic, Vladan Devedzic
Jin-Cheon Na, Tun Thura Thet, Dion Hoe-Lian Goh, Yin-Leng Theng, Schubert Foo
Dion Hoe-Lian Goh, Khasfariyati Razikin, Alton Y.K. Chua, Chei Sian Lee, Schubert Foo
Taha Osman, Dhavalkumar Thakker, Gerald Schaefer
Stephen Kimani, Emanuele Panizzi, Tiziana Catarci, Margerita Antona
Spyros Veronikis, Giannis Tsakonas, Christos Papatheodorou
Mila M. Ramos, Luz Marina Alvaré, Cecilia Ferreyra, Peter Shelton
Robert Neumayer, Andreas Rauber
Gerald Schaefer, Simon Ruszala
Cláudio de Souza Baptista, Ulrich Schiel
Nuria Lloret Romero, Margarita Cabrera Méndez, Alicia Sellés Carot, Lilia Fernandez Aquino
Rubén Béjar, J. Nogueras-Iso, Miguel Ángel Latre, Pedro Rafael Muro-Medrano, F. J. Zarazaga-Soria
O. Cantán Casbas, J. Nogueras-Iso, F. J. Zarazaga-Soria
Piedad Garrido Picazo, Jesús Tramullas Saz, Manuel Coll Villalta
Wan Ab. Kadir Wan Dollah, Diljit Singh
Frances L. Lightsom, Alan O. Allwardt
Stephan Strodl, Christoph Becker, Andreas Rauber
Thomas Lidy, Andreas Rauber
Leonardo Bermón-Angarita, Antonio Amescua-Seco, Maria Isabel Sánchez-Segura, Javier García-Guzmán
Kanwal Ameen, Muhammad Rafiq
Seungwon Yang, Barbara M. Wildemuth, Jeffrey P. Pomerantz, Sanghee Oh
Faisal Ahmad, Tamara Sumner, Holly Devaul
Yongqing Ma, Warwick Clegg, Ann O’Brien
Chang Chew-Hung, John G. Hedberg
Michael B. Twidale, David M. Nichols
Soh Whee Kheng Grace