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Trademark image retrieval method

An image retrieval and trademark technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as inability to correspond, inability to highlight, and problems that have not been better resolved, so as to achieve accurate position definition and improve accuracy The effect of high performance and fast calculation speed

Active Publication Date: 2018-11-13
南昌奇眸科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Although the research on content-based trademark image retrieval is relatively active, and some systems have been put into use, there are still some problems that have not been well resolved.
The biggest difficulty is that there is no correspondence between the low-level image content features extracted by the system and the high-level semantics used by users when searching. people are satisfied
[0005] In the previous manual coding process, trademark certification personnel can weight the coding results according to certain rules. The weights corresponding to important parts of the original trademark are large, so that these important graphics in the original trademark can be highlighted, while the existing ones The system often extracts the global features of the image for matching, and cannot highlight these important information, so the reliability of the system is not high; another important problem is the speed of retrieval. As the number of images in the library increases, the speed of retrieval becomes a constraint A bottleneck of the system, and the cumulative number of existing registered trademarks in my country has exceeded 10 million

Method used

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  • Trademark image retrieval method

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Embodiment 1

[0054] A trademark image retrieval method, comprising the following steps:

[0055] S1: Perform multi-scale feature extraction on the image to be retrieved and the comparison image in the image database;

[0056] S2: Carry out similarity matching between the image features to be retrieved and the compared image features between global scales;

[0057] S3: filter the correct match;

[0058] S4: candidate similar region segmentation;

[0059] S5: Similarity matching between local scales in the region, sorting the comparison images according to the size of the matching similarity.

Embodiment 2

[0061] A trademark image retrieval method, comprising the following steps:

[0062] S1: Multi-scale feature extraction is performed on the image to be retrieved and the comparison image in the image database; multiple sliding windows of different scales are used to segment the regions of the image to be retrieved and the comparison image, and image features in the sliding window window are extracted;

[0063] Include the following steps:

[0064] (1) Extract the gradient direction histogram feature of the image pixel in the sliding window window;

[0065] (2) Gradient orientation histogram quantization encoding;

[0066] (3) Normalization;

[0067] (4) Spatial distribution description, and cascaded gradient direction histogram and spatial distribution.

[0068] S2: Carry out similarity matching between the features of the image to be retrieved and the features of the compared image on a global scale; slide the sliding window in the image to be retrieved, traverse all the wi...

Embodiment 3

[0075] A trademark image retrieval method, comprising the following steps:

[0076] S1: Multi-scale feature extraction is performed on the image to be retrieved and the comparison image in the image database; multiple sliding windows of different scales are used to segment the regions of the image to be retrieved and the comparison image, and image features in the sliding window window are extracted;

[0077] Include the following steps:

[0078] (1) Extract the gradient direction histogram feature of the image pixel in the sliding window window;

[0079] (2) Gradient orientation histogram quantization coding;

[0080] (3) Normalization;

[0081] (4) Spatial distribution description, and cascade gradient direction histogram and spatial distribution;

[0082] Step (1), calculate the horizontal gradient and vertical gradient of the image pixel, using the direction template [-1,0,1], the calculation rule is [G h ,G v ] = gradient(F),

[0083] Step (2), the direction angle...

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Abstract

The invention belongs to the field of image retrieval and particularly relates to a trademark image retrieval method, which comprises the following steps: carrying out multi-scale feature extraction on a to-be-retrieved image and a comparison image in an image library; performing similarity matching between global scales on the characteristics of the to-be-retrieved image and the characteristics of the comparison image; screening correct matching; segmenting a candidate similarity region; carrying out similarity matching between intra-regional partial scales; and sorting the comparison imageswith similar retrieval results. The trademark image retrieval method in the invention is high in retrieval accuracy, low in loss and high in speed.

Description

technical field [0001] The invention belongs to the field of image retrieval, in particular to a trademark image retrieval method. Background technique [0002] Trademark plays a very important role in the industrial and commercial society. It is a symbol of a company, product or service. It is integrated with the product quality, service quality, and management of the enterprise. It becomes a symbol of corporate reputation and an intangible asset. [0003] Trademark retrieval refers to the process of finding images similar to the input trademark image from the existing trademark image database. [0004] Although the research on content-based trademark image retrieval is relatively active, and some systems have been put into use, there are still some problems that have not been well resolved. The biggest difficulty is that there is no correspondence between the low-level image content features extracted by the system and the high-level semantics used by users when searching...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 李建圃樊晓东
Owner 南昌奇眸科技有限公司
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