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Self-adaptive automobile instrument detection method based on character segmentation cascaded quadratic classifier

A two-classifier and character segmentation technology, applied in the field of visual detection of automotive instrument pointers, to achieve the effect of wide application, strong adaptability and high robustness

Active Publication Date: 2018-01-16
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The present invention is to solve the problems existing in the field of automobile instrument detection in the existing instrument detection system, and now provides an adaptive automobile instrument detection method based on character segmentation cascaded two classifiers

Method used

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  • Self-adaptive automobile instrument detection method based on character segmentation cascaded quadratic classifier
  • Self-adaptive automobile instrument detection method based on character segmentation cascaded quadratic classifier
  • Self-adaptive automobile instrument detection method based on character segmentation cascaded quadratic classifier

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specific Embodiment approach 1

[0041] Specific implementation mode one: refer to figure 1 and Figure 4 Describe this embodiment in detail, a kind of adaptive automobile meter detection method based on character segmentation cascade binary classifier described in this embodiment, comprises the following steps:

[0042] Step 1: When the input signal value of the instrument under test is i, the instrument pointer responds to the signal, rotates to obtain the response value, collects the color image of the entire car dial as the original image, and obtains the instrument under test (speedometer or tachometer) in the original image ) of the ROI (Region of Interest, region of interest) image, the ROI image is grayscaled and the Ostu algorithm is used for threshold segmentation to obtain a binary image, and each connected domain of the binary image is binarized and marked, and then Execute step two;

[0043] Step 2: Use the method based on contour analysis to perform fine extraction of instrument pointers on t...

specific Embodiment approach 2

[0057] Specific implementation mode two: refer to figure 2 and 3 This embodiment is described in detail. This embodiment is a further description of the adaptive automobile instrument detection method based on character segmentation cascaded binary classifiers described in the first embodiment. In this embodiment, the instrument pointer in step two is connected. The specific method of obtaining the domain image is as follows:

[0058] Rough pointer extraction is performed on the connected domain with the largest area after binarization marking, and the rough pointer extraction image is obtained.

[0059] Extract the contour of the pointer and roughly extract the image to obtain the contour image,

[0060] The PPHT (Progressive Probabilistic Hough Transform) algorithm is used to fit the contour image to obtain a contour image with a contour fitting line.

[0061] Find the inner contour with the largest area in the contour image with the contour fitting straight line, and ext...

specific Embodiment approach 3

[0062] Specific implementation mode three: refer to Figure 4 This embodiment is described in detail. This embodiment is a further description of a kind of adaptive automobile meter detection method based on character segmentation cascaded two classifiers described in the first embodiment. In this embodiment, in step 4, use the following The formula obtains the intersection point (x k ,y k ):

[0063] (The slope of the two fitting lines k 1 and k 2 both exist)

[0064] (One of the fitted straight lines slope k 2 does not exist)

[0065] Among them, b 1 and b 2 are the intercepts of the two fitted straight lines, k 1 and k 2 are the slopes of the two fitted straight lines, respectively;

[0066]Take the average value of the intersection points of N fitted straight lines as the rotation center of the instrument pointer (x center ,y center ), using the following formula to obtain the center of rotation of the instrument pointer (x center ,y center ),

[0067] ...

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Abstract

The invention discloses a self-adaptive automobile instrument detection method based on character segmentation cascaded quadratic classifier, relating to the automobile instrument pointer visual detection technology field. In order to solve problems of a current instrument detection system in the automobile instrument detection field, the self-adaptive automobile instrument detection method basedon character segmentation cascading performs threshold segmentation on an original image and performs analysis processing on morphology and a connected domain, adopts a method based on couture analysis method to finely extract pointers, establishes a pointer information list, constructs a character segmentation cascading quadratic classifier consisting of an HOG / SVM quadratic classifier, a character filter and a CNN digital classifier which are connected in a cascaded mode, adopts the cascaded quadratic classifier to identify a number character area of the instrument, performs local analysis to extract scale points with the number character area as a center, determines a position of an angle corresponding to the scale point, establishes a Newton interpolation linear description relation between the instrument pointer angle and a response value and determines whether the instrument is qualified. The self-adaptive automobile instrument detection method based on the character segmentationcascaded quadratic classifier is applied to the automobile instrument pointer vision detection field.

Description

technical field [0001] The invention belongs to the technical field of visual detection of automobile instrument pointers. Background technique [0002] As the human-machine interface between the car and the driver, the car instrument is an important part of the car. The response accuracy of the car instrument to the signal will directly affect the safety and comfort of the driving process. The detection of the pointer on the mechanical pointer instrument is one of the most important detection items in the instrument detection. The response accuracy of the instrument pointer to the speed command signal directly determines the quality of the produced instrument. Therefore, the precise measurement of the pointer response requires detection Algorithms have high precision. In addition, automotive meter manufacturers will produce different types of meters, so it is hoped that the detection algorithm will have good versatility and adaptability. [0003] For the detection of the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/34G06K9/38G06K9/62G06V30/10
CPCG06V30/153G06V2201/02G06V30/10G06V10/82G06V30/19173B60K35/28B60K2360/176B60K2360/21B60K2360/60B60K35/90B60K35/10G01D18/002B60K35/00G06N20/00G06T2207/20084G06N3/045B60K35/60
Inventor 高会军伊明于金泳郭丰钰
Owner HARBIN INST OF TECH
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