scholarly journals Iris Location Algorithm Based on Union-Find-Set and Block Search

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Long-yang Huang ◽  
Li-qiang Zhang ◽  
Xiao-li Duan
Keyword(s):  
Image Recognition ◽  
Hough Transform ◽  
Iris Recognition ◽  
Recognition Algorithm ◽  
Original Image ◽  
Localization Algorithm ◽  
Outer Circle ◽  
Convolution Operation ◽  
Gray Histogram ◽  
Location Algorithm

In view of the problem of unstable recognition effect and low robustness of a traditional iris location algorithm, an iris location algorithm based on union-find-set and block search is proposed. Firstly, the inner circle of the iris is roughly positioned by the method of retrieval, and then, the Hough transform is used to accurately locate the pupil. After that, the convolution operation is used to roughly locate the outer circle, and then, the original image is partitioned to search. And the grayscale change in the gray histogram of the screenshot is observed to accurately locate the outer circle. The obtained iris and the iris obtained by the traditional localization algorithm are processed by the same iris recognition algorithm. The results show that the proposed image is more effective in image recognition and has good robustness.

scholarly journals A Positioning Lockholes of Container Corner Castings Method Based on Image Recognition

2017 ◽  
Vol 24 (s3) ◽  
pp. 95-101 ◽  
Author(s):  
Yang Shen ◽  
Weijian Mi ◽  
Zhiwei Zhang
Keyword(s):  
Image Recognition ◽  
Hough Transform ◽  
Color Space ◽  
Original Image ◽  
Surface Color ◽  
International Standard ◽  
Shipping Container ◽  
Fitting Algorithm

Abstract This article proposes a method of locating and recognizing lockholes in shipping container corner castings. This method converts the original image of the containers captured by a camera into the HSV (Hue, Saturation, Value) color space. To reduce the influence of the surface color of the containers and lights from the environment on the locating and recognizing algorithm, most noisy points of the image are filtered by binarization and a morphology opening operation to make the features of the containers clearer in the image. Thus, the container body can be separated from the total image. Then, the position and size of the corner castings are defined through calculation based on the international standard of the shipping container size. Lastly, by using this method, we can locate the corner casting in the image by using the General Hough Transform fitting algorithm onto ellipses.

scholarly journals The Design and Realization of Cherry Tomato Harvesting Robot Based on IOT

2016 ◽  
Vol 12 (12) ◽  
pp. 23 ◽  
Author(s):  
Biqing Li ◽  
Yongfa Ling ◽  
Hongyan Zhang ◽  
Shiyong Zheng
Keyword(s):  
Image Recognition ◽  
Recognition Rate ◽  
Control Technology ◽  
Original Image ◽  
Cherry Tomato ◽  
Modular Control ◽  
Breakage Rate ◽  
Harvesting Efficiency ◽  
Technology Processes ◽  
Harvesting Robot

To improve the efficiency of harvesting cherry tomato and reduce its breakage rate, we design a harvesting robot base on image recognition and modular control. After image acquisition with IOT technology, the binary processing and expansion and corrosion processing of original image can effectively increase the fruit recognition rate. In addition, the use of fuzzy control technology processes the response error of manipulator. We test the performance of cherry tomato harvesting robot through harvesting experiment. The experimental results show that the harvesting efficiency significantly improves and the degree of crushing cherry tomato greatly reduces after using the cherry tomato harvesting robot.

A Study on Safety Helmet Detection Using Image Recognition Algorithm

2020 ◽  
Vol 25 (4) ◽  
pp. 350-357
Author(s):  
Chun-myoung Noh ◽  
Ki-Kwan Kim ◽  
Su-bong Lee ◽  
Dong-hoon Kang ◽  
Jae-chul Lee
Keyword(s):  
Image Recognition ◽  
Recognition Algorithm

Iris Recognition Method Based on Feature Discrimination and Category Correlation

2014 ◽  
Vol 602-605 ◽  
pp. 1610-1613
Author(s):  
Ming Hai Yao ◽  
Na Wang ◽  
Jin Song Li
Keyword(s):  
Iris Recognition ◽  
Predictive Accuracy ◽  
Gabor Filter ◽  
Recognition Algorithm ◽  
Recognition Method ◽  
Texture Characteristic ◽  
Multi Scale ◽  
Laplacian Score ◽  
Circular Gabor Filter ◽  
Academy Of Sciences

With the increasing number of internet user, the authentication technology is more and more important. Iris recognition as an important method for identification, which has been attention by researchers. In order to improve the predictive accuracy of iris recognition algorithm, the iris recognition method is proposed based feature discrimination and category correlation. The feature discrimination and category correlation are calculated by laplacian score and mutual information. The formula about feature discrimination and category correlation are built. Aiming at texture characteristic of iris image, the multi-scale circular Gabor filter is used to feature extraction. The computational efficiency of algorithm is improved. In order to verify the validity of the algorithm, the CASIA iris database of Chinese Academy of Sciences is used to do the experiment. The experimental results show that our method has high predictive accuracy.

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