Cloth image retrieval method based on convolutional neural network

A convolutional neural network and image retrieval technology, applied in the field of fabric image retrieval based on convolutional neural network, can solve the problems of small number of parameters, inability to adapt, and inability to adapt to all types of textile fabric images, etc., to improve the accuracy rate and robustness, reducing the effect of computational complexity

Pending Publication Date: 2020-05-08
苏州正雄企业发展有限公司
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Problems solved by technology

These traditional features require manual experiments to set parameters, and the setting of parameters is not suitable for all types of textile f

Method used

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  • Cloth image retrieval method based on convolutional neural network
  • Cloth image retrieval method based on convolutional neural network
  • Cloth image retrieval method based on convolutional neural network

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[0046] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] ginseng figure 1 Shown, a kind of cloth image retrieval method based on convolutional neural network of the present invention specifically comprises:

[0048] S1. Scale the collected textile fabric image library to a fixed size of 300*300, and classify it as a training sample set;

[0049] S2, designing a convolutional neural network ...

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Abstract

The invention discloses a cloth image retrieval method based on a convolutional neural network, and the method comprises the steps: carrying out preprocessing of a textile fabric image, zooming of theimage through bilinear interpolation, and carrying out the normalization and other preprocessing operations; designing a convolutional neural network as a classifier; training the neural network by using a classified loss function and gradient back propagation iteration to obtain a feature extractor; performing feature extraction on the retrieval graph and the fabric library to obtain a 1024-dimensional feature vector; and calculating the similarity of the two feature vectors by adopting an L2 measurement method, and sorting to realize recognition of textile fabric image retrieval. Accordingto the invention, contour spatial position feature extraction can be carried out on the target shape, and recognition of the target with occlusion is realized. The method has scale invariance, rotation invariance and translation invariance, so that the problem of incomplete contour recognition is effectively solved, and the accuracy and robustness of target recognition and shape retrieval are improved.

Description

technical field [0001] The invention relates to the field of image retrieval, in particular to a cloth image retrieval method based on a convolutional neural network. Background technique [0002] It has always been a challenge for fabric suppliers to quickly find the fabric that is most similar to the incoming sample cloth in a huge number of textile fabric varieties. [0003] One of the traditional search methods for fabrics and textiles is to rely mainly on human eyes. For more skilled master craftsmen, they may also rely on their own memory to speed up the search. However, this method becomes more difficult as the number of textile fabrics increases, and human memory is degraded and fuzzy, and it is prone to frequent mistakes, which affects retrieval efficiency. Another solution is to build an automated retrieval system based on traditional image features, such as image texture features, edge features, hash features, etc. These traditional features require manual exper...

Claims

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Application Information

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IPC IPC(8): G06F16/532G06F16/538G06N3/08G06T3/40
CPCG06F16/532G06F16/538G06N3/084G06T3/4007Y02P90/30
Inventor 夏为民
Owner 苏州正雄企业发展有限公司
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