A new segmentation algorithm based on evolutionary algorithm and bag of words model
by Kangshun Li; Weiguang Chen; Ying Huang; Shuling Yang
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 14, No. 3, 2019

Abstract: Crop disease and insect pest detection and recognition using machine vision can provide precise diagnosis and preventive suggestions. However, the complexity of agricultural pest and disease identification based on traditional bag of words (BOW) models is high and the effect is general. This paper presents a histogram quadric segmentation algorithm based on an evolutionary algorithm to observe the features (colour, texture) of disease spots and to learn from the guided filtering algorithm. This process aims to obtain the precise positions of disease spots in images. Dense-SIFT, which can extract features and spatial pyramid, which can map image features to high-spatial-resolution space, are simultaneously applied in the recognition of crop diseases and insect pests in the BOW model. The experimental results show that the new segmentation algorithm can effectively locate the positions of disease spots in corn images and the improved BOW model substantially increases the recognition accuracy of crop diseases and insect pests.

Online publication date: Mon, 09-Sep-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of High Performance Computing and Networking (IJHPCN):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com