Method and system of detecting and recognizing a vehicle logo based on selective search

Patent metadata

Field	Value
Publication number	US-10255691-B2
Application number	US-201715458186-A
Country	US
Kind code	B2
Filing date	Mar 14, 2017
Priority date	Oct 20, 2016
Publication date	Apr 9, 2019
Grant date	Apr 9, 2019

Abstract

The invention discloses a method and a system of detecting and recognizing a vehicle logo based on Selective Search, the method comprising: positioning a vehicle plate on an original image of a vehicle to obtain a vehicle plate position; coarsely positioning a vehicle logo on the original image to obtain a coarse positioning image of the vehicle logo; selecting vehicle logo candidate areas in the coarse positioning image; performing target positioning in the vehicle logo candidate areas with the Selective Search to obtain a set of target regions; training a vehicle logo location classifier with Spatial Pyramid Matching based on Sparse Coding (ScSPM) to determine the vehicle logo from the set of target regions to obtain a vehicle logo position; and training a multi-class vehicle logo recognition classifier with the ScSPM to conduct a specific type-recognition for the vehicle logo to obtain a vehicle logo recognition result.

First claim

We claim:

1. A method of detecting and recognizing a vehicle logo based on Selective Search, comprising the steps of:
positioning a license plate on an original image of a vehicle to obtain a license plate position;
coarsely positioning a vehicle logo on the original image of the vehicle according to the license plate position, spatial structure between the license plate and the vehicle logo, and vehicle window edge feature, to obtain a coarse positioning image of the vehicle logo;
selecting vehicle logo candidate areas in the coarse positioning image of the vehicle logo based on a central axis of the vehicle;
performing target positioning on the vehicle logo candidate areas with a Selective Search, to obtain a set of target regions, wherein region combination performed with the Selective Search is based on color similarity, texture similarity, size similarity and fill similarity comprehensively;
training a vehicle logo location classifier with Spatial Pyramid Matching based on Sparse Coding (ScSPM), to determine the vehicle logo from the set of target regions, to obtain a vehicle logo position; and
training a multi-class vehicle logo recognition classifier with the Spatial Pyramid Matching based on Sparse Coding (ScSPM) to conduct specific type-recognition for the vehicle logo, to obtain a vehicle logo recognition result;
determining a position of a down boundary for vehicle logo coarse positioning according to a position of an up boundary for vehicle logo coarse positioning, wherein the coordinate of the down boundary, Y down , is determined by a formula Y down =y up , and y up refers to the coordinate of the up boundary;
coarsely positioning a vehicle window according to vertical projection of the original image of the vehicle, to obtain the vehicle window edge feature, and determining a position of the up boundary according to the vehicle window edge feature, the coordinate Y up of the up boundary being determined by a formula:

{

Y
up

=

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2

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2

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1

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1

,

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2

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max
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.
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.

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,

wherein, h(x) refers to the vertical projection of the original image of the vehicle, max 2 h(x) denotes x-coordinates x 1 and x 2 corresponding to two maximum values h(x 1 ) and h(x 2 ) selected from the vertical projection h(x) of

Assignees

• Univ Sun Yat Sen
• Guangdong Fundway Tech Co Ltd

Inventors

• Li Xiying
• Lv Shuo
• Jiang Qianyin
• Luo Donghua
• Yuan Minxian
• Yu Zhi

Classifications

• G06V10/7715

  Feature extraction, e.g. by transforming the feature space, e.g. multi-dimensional scaling [MDS]; Mappings, e.g. subspace methods · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06V10/464 Primary

  using a plurality of salient features, e.g. bag-of-words [BoW] representations · CPC title

• G06T7/73 Primary

  using feature-based methods · CPC title

• G06F18/2136

  based on sparsity criteria, e.g. with an overcomplete basis · CPC title