Image processing and Retrieval Trends

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Sunday, October 12, 2008

Image Processing Journals

Αναρτήθηκε από Savvas Chatzichristofis
  1. IEEE Trans. on Pattern Analysis and Mach. Int.
  2. IEEE Trans. on Image Processing
  3. Pattern Recognition
  4. CVGIP: Computer Vision and Image Understanding
  5. International Journal of Computer Vision
  6. Optical Engineering
  7. Image and Vision Computing
  8. Journal of Digital Imaging
  9. IEEE Trans. on Systems Man and Cybernetic- Part B
  10. Journal of Mathematical Imaging and Vision
  11. Journal of Electronic Imaging
  12. International Journal of Imaging Systems and Technology
  13. Pattern Analysis and Applications
  14. Pattern Recognition Letters
  15. Journal of Imaging Science and Technology
  16. Real-Time Imaging
  17. Engineering Applications of Artificial Intelligence
  18. International Journal of Pattern Recognition and Artificial Intelligence
  19. IEE Proceedings - Vision, Image and Signal Processing
  20. Neural Computing & Applications
  21. Imaging Science Journal
  22. Machine Vision and Applications
  23. International Journal on Document Analysis and Recognition
  24. International Journal of Image and Graphics
  25. Journal of Visual Communication and Image Representation
  26. Journal of Intelligent & Robotic Systems
  27. Electronic Letters

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Compact Composite Descriptors for Content Based Image Retrieval

Img(Rummager)

Img(Rummager)
Img(Rummager) software can be connected with a database and execute a retrieval procedure, extracting the necessary for the comparison features in real time. The image-database can be stored either in the computer where the retrieval is actually taking place, or in a local network. Moreover, this software is capable of executing retrieval procedure among the keyword-based results that FlickR provides. Read More

Img(Anaktisi)

Img(Anaktisi)
In this web-site a new set of feature descriptors is presented in a retrieval system. These descriptors have been designed with particular attention to their size and storage requirements, keeping them as small as possible without compromising their discriminating ability. These descriptors incorporate color and texture information into one histogram while keeping their sizes between 23 and 74 bytes per image. Read More

MMRetrieval.Net

MMRetrieval.Net
In this web application, we present an experimental multimodal search engine, which allows multimedia and multi-language queries, and makes use of the total available information in a multimodal collection. All modalities are indexed and searched separately, and results can be fused with different methods depending on ■the noise and completeness characteristics of the modalities in a collection ■whether the user is in a need of high initial precision or high recall Beyond fusion, we also provide 2-stage retrieval by first thresholding the results obtained by secondary modalities targeting recall, and then re-ranking them based on the primary modality.

TRECFiles Evaluator

TRECFiles Evaluator
TRECFiles Evaluator (ver 0.1 BETA) calculates the efficiency of the MAP, ANMRR, P10, P20 and the MNRO in TREC Files (Trec Format), giving also to the user the ability to execute significance tests (ST). STs tell us whether an observed effect, such as a difference between two means or a correlation between two variables, could reasonably occur just by chance in selecting a random sample. This application uses a bootstrap test, one-tailed, at significance levels 0.05, 0.01, and 0.001, against a baseline run.



Compact Composite Descriptors (CCD) is a recently proposed set of descriptors that combine more than one features in one histogram. These Descriptors forms the Part 1 of a new Visual Multimedia Content Description Scheme (VICODEs). VICODEs is proposing a set of descriptors for each kind of images.

Download the latest Version of MPEG-7 Descriptors for C#. The implementation of these descriptors is based on Lire image retrieval System (Lire). Download the Descriptors

The LIRE (Lucene Image REtrieval) library provides a simple way to retrieve images and photos based on their color and texture characteristics. LIRE creates a Lucene index of image features for content based image retrieval (CBIR). Three of the available image features are taken from the MPEG-7 Standard: ScalableColor, ColorLayout and EdgeHistogram a fourth one, the Auto Color Correlogram has been implemented based on recent research results. Furthermore simple methods for searching the index and result browsing are provided by LIRE. The LIRE library and the LIRE Demo application as well as all the source are available under the Gnu GPL license.

CSPD is a MPEG-like descriptor that contains conventional contour and region shape features with a wide applicability from any arbitrary shape to document retrieval through word spotting. It is also, compact (it less than 16 bytes) and requires low computational cost. The obtained retrieval results are satisfactory in comparison with other MPEG-7 shapes descriptors. Particular, it has been designed with attention to its size and storage requirements, keeping it as small as possible without limiting its discriminating ability.


Several image processing and retrieval examples using c#

This technique performs the word matching directly in the document images bypassing OCR and using word-images as queries. The entire system consists of the Offline and the Online procedures. In the Offline procedure, the document images are analyzed and the results are stored in a database. Three main stages, the preprocessing, the word segmentation and the feature extraction stages, constitute the offline procedure.

Caliph & Emir Caliph & Emir are MPEG-7 based Java prototypes for digital photo and image annotation and retrieval supporting graph like annotation for semantic metadata and content based image retrieval using MPEG-7 descriptors Read More

Image processing useful links

Image Processing Journals

Image Retrieval Systems

Benchmark databases for CBIR

Blogs/Web Sites I Follow/Suggest

Dr. George Sirakoulis Web Page and Blog

Dr Konstantinos Zagoris Web Page

Dr Avi Arampatzis Web Page

Dr Vasilios Vonikakis Web Page

Dr Oge Marques Blog

PIXEL SHAKERS

Dr Christian Timmerer Blog


Practical Image and Video Processing Using MATLAB® by Oge Marques

DUTH Robotics Team

DUTH Robotics Team
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