University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Performance evaluation of image filtering for classification and retrieval

Schubert, F and Mikolajczyk, K (2013) Performance evaluation of image filtering for classification and retrieval In: ICPRAM 2013, 2013-02-15 - 2013-02-18, Barcelona, Spain.

icpram_2013_camready.pdf - ["content_typename_UNSPECIFIED" not defined]
Available under License : See the attached licence file.

Download (877kB) | Preview
PDF (licence)
Available under License : See the attached licence file.

Download (33kB) | Preview


Much research effort in the literature is focused on improving feature extraction methods to boost the performance in various computer vision applications. This is mostly achieved by tailoring feature extraction methods to specific tasks. For instance, for the task of object detection often new features are designed that are even more robust to natural variations of a certain object class and yet discriminative enough to achieve high precision. This focus led to a vast amount of different feature extraction methods with more or less consistent performance across different applications. Instead of fine-tuning or re-designing new features to further increase performance we want to motivate the use of image filters for pre-processing. We therefore present a performance evaluation of numerous existing image enhancement techniques which help to increase performance of already well-known feature extraction methods. We investigate the impact of such image enhancement or filtering techniques on two state-of-the-art image classification and retrieval approaches. For classification we evaluate using a standard Pascal VOC dataset. For retrieval we provide a new challenging dataset. We find that gradient-based interest-point detectors and descriptors such as SIFT or HOG can benefit from enhancement methods and lead to improved performance.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Date : 2013
Contributors :
Additional Information : Paper submitted to the 2nd International Conference on Pattern Recognition Applications and Methods Barcelona, 2013.
Depositing User : Symplectic Elements
Date Deposited : 15 Oct 2014 17:17
Last Modified : 16 Oct 2014 01:33

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800