Method for extracting regions of interest of pedestrian by using image segmentation method on the basis of road restriction

A region of interest and image segmentation technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as time-consuming, long algorithm execution time, complex multi-layer classifier algorithm, etc., to reduce detection time, detect The effect of shortening the time

Active Publication Date: 2016-01-20
CHANGCHUN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

It describes an improved way that uses images from cameras or sensors to detect people's presence within their environment quickly without being affected by external factors like weather patterns or sunlight levels. By utilizing this technique, it can reduce false alarms caused by poorly lit indoor environments such as stalls at restaurants or shops where there may be multiple individuals who want privacy protection during shopping hours. Overall, these techniques help streamline security measures and make sure everyone has access rights when they shouldn’t take them outdoors.

Problems solved by technology

Technic Problem addressed in this patents are how to improve automatic vehicle systems like cars or drones with detectable paces around them while reducing their response time during raster scan. Current methods have limitations due to factors including slow searching process, poorly identified regions containing irrelevant data, high computational complexity, difficulty in analyzing multiple scenes simultaneously, etc., resulting in reduced accuracy and reliability of automobile navigation systems.

Method used

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  • Method for extracting regions of interest of pedestrian by using image segmentation method on the basis of road restriction
  • Method for extracting regions of interest of pedestrian by using image segmentation method on the basis of road restriction
  • Method for extracting regions of interest of pedestrian by using image segmentation method on the basis of road restriction

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Experimental program
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Embodiment Construction

[0046] 1. Read in the image to be detected I

[0047] 2. Determine whether the image I is a grayscale image, if it is implemented in step 3, if it is not, it will be converted into a grayscale image I gray ,Such as figure 2 , which is the converted grayscale image.

[0048] 3. For Image I gray Image I obtained after median filtering med ;

[0049] This implementation mode uses a 3*3 median filter template, and the median filter model

[0050] as g(mx,my)=med{f(mx-3,my-3)(1)

[0051] Where g(mx,my) represents the processed image f(mx-3,my-3) represents the pixel value in the 3*3 field of the original image centered on (mx,my), and the Med operation is to take the median value of the pixel operation, such as image 3 As shown, it is the effect after median filtering;

[0052] 4. Use histogram equalization technology to image I med Carry out grayscale enhancement, the enhanced image I histeq ;

[0053] Histogram equalization is used to improve image contrast to achiev...

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Abstract

The invention relates to a method for extracting the regions of interest (ROIs) of a pedestrian by using an image segmentation method on the basis of road restriction and belongs to the field of vehicular pedestrian detection ROIs extraction. The method comprises steps of: reading an image I to be detected; determining whether the image I is a grayscale image; performing median filtering on the image I<gray> in order to obtain an image I<med>; performing grayscale enhancement on the image I<med> by using histogram equalization; training an optimal grayscale image segmentation threshold value of a common driving image by using a fuzzy C-means clustering algorithm; obtaining a binary image; performing edge detection on an image I<Bgrow>; performing Hough transformation on an image I<edge> in order to obtain a linear equation for cutting pavements; marking the communication regions of an image I<hough>; extracting possibly-existing ROIs of the pedestrian; performing HOG+SVM on the extracted ROIs in order to perform accurate pedestrian detection; and drawing a rectangular frame with a size of 128*64 pixel2 on the original image I. The method effectively decreases the number of traversal windows so as to improve detection speed and detection precision.

Description

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Claims

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Application Information

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Owner CHANGCHUN UNIV OF TECH
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