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Pedestrian identification method based on image with FHOG- LBPH feature

A pedestrian recognition and feature image technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of redundant information, high feature dimension, and affecting pedestrian detection speed, etc., to achieve stable texture features and improve Effects on accuracy, enhanced processing power, and robustness

Inactive Publication Date: 2017-05-17
北京细推科技有限公司
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AI Technical Summary

Problems solved by technology

But at present, for the detection of histogram of gradient orientation (HOG) and local binary pattern (LBP), there are problems such as high feature dimension, redundant information, and affecting the detection speed of pedestrians in video images.

Method used

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  • Pedestrian identification method based on image with FHOG- LBPH feature
  • Pedestrian identification method based on image with FHOG- LBPH feature
  • Pedestrian identification method based on image with FHOG- LBPH feature

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Experimental program
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Embodiment Construction

[0021] Combine below figure 1 , 2 A kind of image pedestrian recognition method based on FHOG-LBPH feature of the present invention is described further:

[0022] Step 1: FHOG feature extraction; calculate the statistical value of the direction information of the local image gradient, and represent the outline information of the pedestrian.

[0023] In step 1.1, the input image is normalized using the Gamma method.

[0024]

[0025] Among them, I(x,y) represents the gray value of the current pixel. The purpose is to adjust the contrast of the image, reduce the influence of local shadows and illumination changes in the image, and at the same time suppress the interference of noise.

[0026] Step 1.2, pixel gradient calculation.

[0027] The calculation of FHOG features is very sensitive to the template operator. After comparison, it is found that the simplest one-dimensional discrete differential template (-1, 0, +1) and its transpose perform gradients on each pixel of t...

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Abstract

The invention provides a pedestrian identification method based on image with FHOG-LBPH feature. By statistical average of fusion HOG features (FHOG) , the optimal features are selected according to the combination with single optimal feature and the separable criterion of bhattacharyya distance, and improved FHOG-LBPH feature are obtained through fusion LBPH characteristics, fundamentally reducing the feature dimension; A classifier is obtained by using a support vector machine (SVM) to train the sample characteristics in order to obtain the classification of the test sample. The experimental results show that the method makes the pedestrian detection accuracy and real-time performance a certain improvement. Effectiveness of the method is validated by the image automatically shot, and the method has certain application value in the real pedestrian recognition.

Description

[0001] 1. Technical field: [0002] The invention provides an image pedestrian recognition method based on FHOG-LBPH features, which belongs to the technical field of computer vision monitoring. [0003] 2. Background technology: [0004] Pedestrian detection is an important research direction in the field of computer vision and pattern recognition. It has good application value in the fields of intelligent transportation, video surveillance, crowd safety prediction and management, robots and advanced human-computer interaction. Since the human body is a non-rigid target, it is easily affected by posture, clothing, vision, lighting, etc., and the complex background environment will affect the accuracy of pedestrian detection. Therefore, how to quickly and accurately detect pedestrians from video images , is still a research hotspot. [0005] Among the technical methods of pedestrian detection, the detection method based on machine learning is currently the mainstream method. ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/23G06F18/2411G06F18/253
Inventor 柳宁
Owner 北京细推科技有限公司
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