AR-assisted intelligent analysis and identification system for mobile vegetables diseases based on HOG-SVM

Chao Ma; Lin-yi Li; Yun-sheng Wang; Yong Liu; Shi-pu Xu

doi:10.1117/12.2668866

1 March 2023 AR-assisted intelligent analysis and identification system for mobile vegetables diseases based on HOG-SVM

Chao Ma, Lin-yi Li, Yun-sheng Wang, Yong Liu, Shi-pu Xu

Proceedings Volume 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022); 1258815 (2023) https://doi.org/10.1117/12.2668866
Event: International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 2022, Chongqing, China

Abstract

Aiming at the shortcomings of traditional disease recognition systems that require high shooting environment and large number of samples, this research designs a set of AR-assisted recognition schemes based on HOG-SVM. Under the premise of a small amount of material, due to the introduction of AR technology in the diagnostic system to assist shooting, this solution is better than other methods in terms of training time, recognition speed and average accuracy. Taking the Android terminal as an example, an AR-assisted HOG-SVM-based mobile vegetables disease identification system is implemented, which can quickly identify diseases and guide users to improve the quality of photographed pictures. Through the identification of disease spots in batches of images, the results of disease spot recognition are analyzed from the three aspects of disease accuracy, diseased leaf detection rate and disease spot location accuracy. Finally, AR technology and rapid identification scheme based on HOG-SVM are obtained. The combination can give faster training results and recognition results under the premise of small training samples. Its average accuracy is also higher than deep models such as YOLO v3, SSD 512, and Fast R-CNN. It is a more suitable method for disease identification on the current mobile terminal.

Citation Download Citation

Chao Ma, Lin-yi Li, Yun-sheng Wang, Yong Liu, and Shi-pu Xu "AR-assisted intelligent analysis and identification system for mobile vegetables diseases based on HOG-SVM", Proc. SPIE 12588, International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2022), 1258815 (1 March 2023); https://doi.org/10.1117/12.2668866

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Diseases and disorders

Augmented reality

Education and training

Histograms of oriented gradient

Feature extraction

Image segmentation

Video

Show All Keywords

Keywords/Phrases

Search In:

Publication Years