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Image identifying method and system

A technology of image recognition and window image, which is applied in the field of image recognition methods and systems, and can solve problems such as high misjudgment rate and large amount of calculation for multiple feature combinations

Active Publication Date: 2014-03-26
深圳市弘志拓新创业投资企业(有限合伙)
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AI Technical Summary

Problems solved by technology

[0005] 1. The calculation of multiple feature combinations is large
[0006] 2. In the case of ensuring a low miss rate (Miss Rate), the false positive rate (False Positive) of the system is still high

Method used

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  • Image identifying method and system

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Embodiment Construction

[0040] see figure 1 , which is a flow chart of the steps of the image recognition method of an embodiment, including the following steps:

[0041] Step S101 , acquiring an image, and scanning the image through scanning windows of different sizes to obtain multiple window images.

[0042] Step S102, extracting HOG-LBP feature [Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP)] vectors of each window image.

[0043] In step S103, the plurality of HOG-LBP feature vectors are sequentially identified by a preset HOG-LBP classifier, and a plurality of window images initially determined as objects are obtained.

[0044] Step S104 , extracting the image features of the plurality of window images that are preliminarily determined to be targets through a preset PHOW (Pyramid Histogram of Words) dictionary.

[0045] Step S105, identifying the image features of the plurality of window images through a preset PHOW classifier, filtering out non-target window images, an...

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Abstract

The invention discloses an image identifying method comprising the following steps: scanning an image through scanning windows of different sizes to obtain a plurality of window images; extracting the HOG-LBP (Histograms of Oriented Gradients-Local Binary Pattern) feature vector of each window image; sequentially identifying the HOG-LBP feature vectors through a preset HOG-LBP classifier to obtain a plurality of window images preliminarily judged to be targets; extracting image features of the window images preliminarily judged to be the targets through a preset PHOW (Pyramid Histogram Of Words) dictionary; identifying the image features of the window images through a preset PHOW classifier to obtain a target image window image; clustering to obtain a target image. The invention further provides a image identifying system corresponding to the image identifying method. The window images are filtered by the two classifiers in a cascade way, so that the problem of large calculation amount of simultaneously scanning and calculating various window features on full image and multiscale is solved; the PHOW classifier is independent of the HOG-LBP classifier, so that the misjudgment rate is reduced.

Description

technical field [0001] The invention relates to image processing and analysis technology, in particular to an image recognition method and system. Background technique [0002] Image recognition, such as pedestrian detection, is an important direction of machine vision research at present. Detecting and tracking pedestrians has been used more and more in people's lives, including intelligent transportation and monitoring, automatic robot detection, caring for the elderly, and Currently popular search based on image content, etc. The current popular technology is to use the binary classification method, that is, to scan the image with a window, and then use the trained classifier to judge whether the window is a pedestrian or a non-pedestrian. [0003] At present, a large number of effective algorithms are based on HOG (Histograms of Oriented Gradients, histogram of oriented gradients). Some other features are combined with HOG features to form a series of new detection met...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00
Inventor 马颖东邓亮陈先开
Owner 深圳市弘志拓新创业投资企业(有限合伙)
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