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Method and system for searching images by images based on deep learning

A deep learning and image technology, applied in the field of image search based on deep learning, can solve problems such as difficult control of high-level features, and achieve the effect of meeting the needs of fast analysis, fast search results, and reducing impact

Active Publication Date: 2015-06-03
武汉众智数字技术有限公司
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AI Technical Summary

Problems solved by technology

The deep network described in the document "ImageNet Classification with Deep Convolutional Neural Networks" solves the problem of feature extraction to a certain extent, but because the high-level features are often too abstract and difficult to control, it is necessary to further solve the problem of controlling the high-level features generated by the deep network. in image search

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  • Method and system for searching images by images based on deep learning

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Embodiment 1

[0025] Embodiment 1 of the present invention provides a deep learning-based image search system, such as figure 1 As shown, it includes an image input platform 10, an integrated access gateway 20, an intelligent management server 30 and an intelligent analysis server 40, and the image input platform 10, the integrated access gateway 20, the intelligent management server 30 and the intelligent analysis server 40 are connected in sequence, specific:

[0026] The image input platform 10 is used for image entry, image transmission, image storage and image preprocessing; the integrated access gateway 20 is used for statistical access of the image input platform to the intelligent management server; the intelligent management The server 30 is used to manage and analyze resources; the intelligent analysis server 40 is a functional entity of image search, composed of multiple image analysis units, and each image analysis unit can independently complete the analysis of an image input p...

Embodiment 2

[0028] Embodiment 2 of the present invention provides a deep learning-based image search method, which is characterized in that it includes:

[0029] In step 201, image category features are calculated, and the trained deep convolutional neural network is used to extract classification features from the input image;

[0030] In step 202, the image self-encoding feature is calculated, and the encoded feature is extracted from the input image using the trained automatic encoding algorithm of deep learning;

[0031] In step 203, the mixed feature coding is compressed, the classification feature and the image self-encoding feature are integrated, and these features are encoded by a deep learning automatic encoding algorithm;

[0032] In step 204, the image similarity is calculated according to the features and the output is sorted.

[0033] This embodiment uses the deep convolutional neural network to generate high-level features to help analyze image categories and ensure that t...

Embodiment 3

[0047] Embodiment 3 of the present invention provides specific implementation methods for the implementation of Embodiment 1 and Embodiment 2 in combination with actual cases. It specifically includes five parts as described in Embodiment 2: calculating image category features, calculating image self-encoding features, calculating self-defined features, mixing feature encoding compression, and calculating image similarity and sorting output.

[0048] Part 1: Computing image category features

[0049] The algorithm for calculating image category features uses a deep convolutional neural network, such as the "ImageNet Classification with Deep Convolutional Neural Networks" algorithm described in the article. The network consists of 5 convolutional layers and 3 fully connected layers. The image passes through the convolutional layer and The fully connected layer finally obtains the method of high-level image features, which are mainly used for image classification.

[0050] The ...

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Abstract

The invention relates to the technical field of image searching and provides a method for searching images by images based on deep learning. The method comprises the following steps: calculating image category features, and performing classification feature extraction on input images by using a trained deep convolutional neural network; calculating image coding features, and performing coding feature extraction on the input images by using a trained deep learning automatic coding algorithm; compacting mixed feature codes, integrating the classification features and the image own coding features, and coding the integrated features by a deep learning automatic coding algorithm; calculating image similarity according to the features, and ranking and outputting the image similarity. According to the method disclosed by the invention, advanced features are generated by the deep convolutional neural network, so the similarity of the results of searching images by images in image category is guaranteed; low-level image coding features are generated by using the automatic coding algorithm, so the similarity of the images in content is guaranteed; according to the mixed own coding feature method, the classification features and the image own coding features are further fused, so that the dimensionality is reduced, and the search result is carried out more quickly and more stably.

Description

【Technical field】 [0001] The present invention relates to the technical field of image search, in particular to a method and system for image search based on deep learning. 【Background technique】 [0002] Search by image is a technology to retrieve similar images by inputting images, and provides users with a search technology for searching related graphic and image data. It involves many disciplines such as database management, computer vision, image processing, pattern recognition, information retrieval and cognitive psychology. Its related technologies mainly include two key technologies: feature representation and similarity measurement. It is widely used in various fields such as big data graphic image retrieval, video detection, Internet, shopping search engine and so on. [0003] The image search method based on mixed depth features mainly includes two steps: one is feature extraction, which extracts reliable and stable features to express image content; the other i...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06N3/02
Inventor 孙宇贺波涛于强
Owner 武汉众智数字技术有限公司
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