Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Genetic Algorithms Based Classifier for Object Classification in Images
Date
2011-09-28
Author
Yilmaz, Turgay
Yildirim, Yakup
Yazıcı, Adnan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
182
views
0
downloads
Cite This
Increase in the use of digital images has shown the need for modeling and querying the semantic content, which is usually defined using the objects in the images. In this paper, a Genetic Algorithm (GA) based object classification mechanism is developed for extracting the content of images. Objects are defined by using the Best Representative and Discriminative Feature (BRDF) model, where features are MPEG-7 descriptors. The classifier improves itself in time, with the genetic operations of GA.
Subject Keywords
Descriptors
,
Retrieval
,
Object classification
,
Genetic operations
,
Multiple categorization approach
,
Effectiveness correction factor
URI
https://hdl.handle.net/11511/45995
DOI
https://doi.org/10.1007/978-1-4471-2155-8_66
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
A rule-based method for object segmentation in video sequences
Alatan, Abdullah Aydın; Onural, L (1997-01-01)
Object segmentation and tracking are problems within the scope of MPEG-4 and MPEG-7 standardization activities. A novel algorithm for both object segmentation and tracking is presented. The algorithm fuses motion, color, and accumulated previous segmentation data at 'region level', in contrast to conventional 'pixel level' approaches. The information fusion is achieved by a rule-based region processing unit which intelligently utilizes the motion information to locate the objects in the scene, the color inf...
New models and inference techniques for Gaussian process-based extended object tracking
Kumru, Murat; Özkan, Emre; Department of Electrical and Electronics Engineering (2022-9-09)
In this thesis, we consider the problem of tracking dynamic objects with unknown shapes using point cloud measurements generated by, e.g., lidars, radars, and depth cameras. The point measurements do not only convey information about the object pose, i.e., position and orientation, but they also naturally reveal the characteristics of its latent extent. Aiming to harness the full potential of the available information, we investigate the Gaussian process-based extended object tracking (GPEOT) framework. W...
A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images
SİKUDOVA, Elena; POULİ, Tania; ARTUSİ, Alessandro; Akyüz, Ahmet Oğuz; BANTERLE, Francesco; Mazlumoglu, Zeynep Miray; REİNHARD, Erik (2016-07-01)
An integrated gamut- and tone-management framework for color-accurate reproduction of high dynamic range images can prevent hue and luminance shifts while taking gamut boundaries into consideration. The proposed approach is conceptually and computationally simple, parameter-free, and compatible with existing tone-mapping operators.
A semantic backend for content management systems
LALECİ ERTÜRKMEN, GÖKÇE BANU; Aluc, G.; Dogac, A.; SINACI, ALİ ANIL; Kılıç, Özgün Ozan; Tuncer, F. (2010-12-01)
The users of a content repository express the semantics they have in mind while defining the content items and their properties, and forming them into a particular hierarchy. However, this valuable semantics is not formally expressed, and hence cannot be used to discover meaningful relationships among the content items in an automated way. Although the need is apparent, there are several challenges in explicating this semantics in a fully automated way: first, it is difficult to distinguish between data and...
A real time, low latency, FPGA implementation of the 2-D discrete wavelet transformation for streaming image applications
Benderli, O; Tekmen, YC; Ismailoglu, N (2003-09-06)
In this paper, we present an architecture and a hardware implementation of the 2-D Discrete Wavelet Transformation (DWT) for applications where row-based raw image data is streamed in at high bandwidths and local buffering of the entire image is not feasible. The architecture is especially suited for multi-spectral imager systems, such as on board an imaging satellite, however can be used in any application where time to next image constraints require real-time processing of multiple images. The latency tha...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
T. Yilmaz, Y. Yildirim, and A. Yazıcı, “A Genetic Algorithms Based Classifier for Object Classification in Images,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/45995.