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Logo Recognition Using CNN Features

  • Simone Bianco
  • Marco Buzzelli
  • Davide MazziniEmail author
  • Raimondo Schettini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

In this paper we propose a method for logo recognition based on Convolutional Neural Networks, instead of the commonly used keypoint-based approaches. The method involves the selection of candidate subwindows using an unsupervised segmentation algorithm, and the SVM-based classification of such candidate regions using features computed by a CNN. For training the neural network we augment the training set with artificial transformations, while for classification we exploit a query expansion strategy to increase the recall rate. Experiments were performed on a publicly-available dataset that was also corrupted in order to investigate the robustness of the proposed method with respect to blur, noise and lossy compression.

Keywords

Convolutional Neural Network Query Expansion Lossy Compression Logo Image Logo Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Simone Bianco
    • 1
  • Marco Buzzelli
    • 1
  • Davide Mazzini
    • 1
    Email author
  • Raimondo Schettini
    • 1
  1. 1.DISCo (Dipartimento di Informatica, Sistemistica E Comunicazione)Universitàdegli Studi di Milano-BicoccaMilanoItaly

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