scholarly journals Image recognition in online monitoring of power equipment

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141990083
Author(s):  
Guifeng Wu ◽  
Miao Yu ◽  
Wangwang Shi ◽  
Shengquan Li ◽  
Jiatong Bao
Keyword(s):  
Image Recognition ◽  
Template Matching ◽  
Online Monitoring ◽  
Source Image ◽  
Power Equipment ◽  
Target Image ◽  
Matching Algorithm ◽  
Matching Process ◽  
Abnormal State ◽  
Fast Recognition

The application of remote digital video surveillance and image recognition technology in online monitoring of power equipment is conducive to timely equipment maintenance and troubleshooting. In order to solve the problem of slow speed and large amount of computation of traditional template matching algorithm for power image recognition, a second template matching algorithm for fast recognition of target image is proposed in this article. Firstly, a quarter of the template data is taken and matched within a quarter of the source image, and a reasonable error threshold is given in the matching process. Then, the neighborhood of the minimum error point in rough matching is matched to get the final result. Finally, the algorithm is applied to identify the power equipment and detect the abnormal state of the power equipment. The experimental results show that the matching algorithm can not only accurately locate and identify power equipment and detect equipment faults, but also greatly improve the matching speed compared with other commonly used template matching algorithms.

Research of an Improved Snail Image Recognition Method Based on Grayscale Template Matching

2013 ◽  
Vol 433-435 ◽  
pp. 700-704
Author(s):  
Yin E Zhang
Keyword(s):  
Template Matching ◽  
Source Image ◽  
Complex Environment ◽  
Recognition Method ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Template Image ◽  
Traditional Algorithm ◽  
Template Selection

As the lack in the accuracy and speed of the template matching algorithm for the snail image in the complex environment, the snail source image and the template image have the appropriate scaling in order to improve their sizes in the traditional algorithm. The new algorithm avoids the very big and accurate characteristics about the snail images through shrinking the source images down. The grayscale template matching method is put forward based on the traditional template selection set to prevent that the error caused by human factors on the selected template, the redundancy between the templates is removed in a large extent, further the accuracy of the matching is improved, and the matching time is reduced greatly in the case of matching accuracy guarantee.

scholarly journals Angle and Scale Invariant Template Matching for Handling Image Distortions

2018 ◽  
Vol 7 (2.24) ◽  
pp. 102
Author(s):  
Badrinaathan J ◽  
L N.B.Srinivas
Keyword(s):  
Template Matching ◽  
Histogram Equalization ◽  
Vital Role ◽  
Source Image ◽  
Image Patch ◽  
Scale Invariant ◽  
Matching Algorithm ◽  
Template Image ◽  
Computer Vision Applications

Template matching is a diagnostic approach for detecting a patch of a template image in a given source image. This plays a vital role in multitudinal computer vision applications. In this paper, we propose a methodology that makes the naive template matching algorithm scale and angle invariant during the image recognition process where the source and template is converted to gray scale which makes the technique enhance its proficiency. The proposed algorithm handles the arbitrary modulations of the image patch with respect to size and angle by an exhaustive search of all combinations of sizes are done along with populous combinations of angles. The images adapted are subjected to certain filtering and convolution methods which deepens the quality of the images which in turn assists in retrieving the features with accuracy. The image intensities are adjusted using histogram equalization to enhance the image contrast. These images are then subjected to perform template matching using normalized cross correlation to measure similarity between those two images.  

Research of Hot Stamping Image Recognition Algorithm Based on Projection Feature

2013 ◽  
Vol 469 ◽  
pp. 240-245
Author(s):  
Dong Juan Zhang ◽  
Wan You Tang
Keyword(s):  
Image Recognition ◽  
Template Matching ◽  
Hot Stamping ◽  
Adaptive Threshold ◽  
Recognition Algorithm ◽  
Line Detection ◽  
Matching Process ◽  
Quality Detection ◽  
On Line ◽  
Rgb Images

To meet the requirements of real-time on-line detection, an algorithm for hot stamping image recognition was proposed based on projection with adaptive threshold. Firstly CCD collects digital image, then convert RGB images into HSV space, and extract V channel. The initial threshold was set according to the error on the first location of matching region. In the subsequent template matching process, the threshold would be update; the smallest D-value point is the best match. The experiment results show that the improved algorithms can identify hot stamping area and greatly increase the matching velocity, having certain guiding significance to hot stamping quality detection based on machine vision.

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