Visual Database Design: Indexing Methods

The paper describes the indexing algorithm suitable for organization of database which contains a large amount of visual information. This approach can be applied to the hybrid database design method which was proposed by the authors in previous publications. Analysis of existing methods shows that the most effective algorithm in this case is B+ tree indexing method. The basic database operations with use of this algorithm are developed. Comparison with other possible approaches is discussed. Directions of the future research are identified.

[1]  James Jones,et al.  A Hybrid Model for Image Databases , 2014, 2014 Enterprise Systems Conference.

[2]  Larisa Bulysheva,et al.  Enterprise systems in Russia: 1992–2012 , 2013, Enterp. Inf. Syst..

[3]  Alexander Bulyshev,et al.  Modeling Segmentation Algorithm , 2012 .

[4]  Larisa Bulysheva,et al.  Segmentation modeling algorithm: a novel algorithm in data mining , 2012, Inf. Technol. Manag..

[5]  Y. L. Liu,et al.  A Robust Image Hashing Algorithm Resistant Against Geometrical Attacks , 2013 .

[6]  Linda G. Shapiro,et al.  Object and concept recognition for content-based image retrieval , 2005 .

[7]  Lida Xu,et al.  Internet of Things for Enterprise Systems of Modern Manufacturing , 2014, IEEE Transactions on Industrial Informatics.

[8]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[9]  Gadadhar Sahoo,et al.  A Modified and Memory Saving Approach to B+ Tree Index for Search of an Image Database based on Chain Codes , 2010 .

[10]  Lida Xu,et al.  Enterprise Information Systems Architecture—Analysis and Evaluation , 2013, IEEE Transactions on Industrial Informatics.

[11]  Chi-Ho Chan,et al.  Fabric defect detection by Fourier analysis , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).

[12]  C. K. Yuen,et al.  Theory and Application of Digital Signal Processing , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  Lida Xu,et al.  Business Intelligence for Enterprise Systems: A Survey , 2012, IEEE Transactions on Industrial Informatics.

[14]  Ying Liu,et al.  A survey of content-based image retrieval with high-level semantics , 2007, Pattern Recognit..

[15]  Zhuming Bi,et al.  A new approach for image databases design , 2017, Inf. Technol. Manag..

[16]  Robert L. Kruse,et al.  Data structures and program design in C , 1986 .

[17]  Lida Xu,et al.  Enterprise Systems: State-of-the-Art and Future Trends , 2011, IEEE Transactions on Industrial Informatics.

[18]  Ian H. Witten,et al.  Managing Gigabytes: Compressing and Indexing Documents and Images , 1999 .

[19]  Larisa Bulysheva,et al.  Image Database Management Architecture: Logical Structure and Indexing Methods , 2017, CONFENIS.

[20]  Ashish Oberoi,et al.  Content Based Image Retrieval System for Medical Databases (CBIR-MD) - Lucratively tested on Endoscopy, Dental and Skull Images , 2012 .

[21]  Ramarathnam Venkatesan,et al.  Robust image hashing , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).