Web Image Extractor

Image feature signatures extractor demo implemented in web browser

Martin Kruliš

Description

This demo presents a feature extraction method that captures color and texture information from an image and produces adaptive signatures for similarity search models, where distances like SQFD or EMD can be used. The method and its parallel implementation for GPUs is presented in our publication (listed below). We are currently transforming the code, so it can be used as OpenCV module.

The demo is also a proof of concept that goes against the current trends in web applications. We propose to offload computations from the servers (or cloud) to end users by performing computationally demanding tasks in the browser. In this case, we claim that in a web application that collects the images from the users, the feature extraction process can be performed by the browser while the image is being uploaded.

Where to get it

The demo is available online -- see the links below. The demo is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Links:

Contact email:

krulis<at>ksi.mff.cuni.cz

Research

Research group at the department:

SImilarity RETrieval Research Group

Supporting research projects and grants:

GACR P103-14-14292P

Publications:

  • Kruliš M.: Is There a Free Lunch for Image Feature Extraction in Web Applications, in Similarity Search and Applications, Glasgow, Springer, ISBN: 978-3-319-25086-1, ISSN: 0302-9743, pp. 283-294, 2015 - text
  • Kruliš M., Lokoč J., Skopal T.: Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures, in Multimedia Tools and Applications, Vol. 2015, Num. 27.6.2015, ISSN: 1380-7501, pp. 1-33, 2015 - text
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