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

170
views

0
downloads

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

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.