Object recognition based on Google's reverse image search and image similarity

András Horváth

doi:10.1117/12.2228505

9 December 2015 Object recognition based on Google's reverse image search and image similarity

András Horváth;

Author Affiliations +

Proceedings Volume 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015); 98170Q (2015) https://doi.org/10.1117/12.2228505
Event: Seventh International Conference on Graphic and Image Processing, 2015, Singapore, Singapore

Abstract

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

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András Horváth, "Object recognition based on Google's reverse image search and image similarity", Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170Q (9 December 2015); doi: 10.1117/12.2228505; https://doi.org/10.1117/12.2228505

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