Apple image fusion algorithm based on binocular acquisition system. (6th October 2022)
- Record Type:
- Journal Article
- Title:
- Apple image fusion algorithm based on binocular acquisition system. (6th October 2022)
- Main Title:
- Apple image fusion algorithm based on binocular acquisition system
- Authors:
- Liu, Liqun
Zhou, Yubo
Gu, Renyuan - Abstract:
- To solve the problem that single natural scene image acquisition information in an orchard cannot meet the requirements of accurate fruit recognition and target positioning, a new apple image fusion algorithm based on the binocular acquisition system named New Non-sub-sampled Contourlet Transform algorithm is proposed to obtain a high-quality fusion image. The binocular acquisition system is constructed with the Time of Flight industrial camera and the colour camera. In order to achieve a better fusion effect, a parameter optimisation algorithm based on an Artificial Bee Colony algorithm with discard strategy for brightness saliency function is proposed to optimise the low-frequency component parameters of the new fusion coefficient rule. The experiments were taken on series of apple images under three sunlight conditions in the orchard. The experimental results show that the six evaluation indicators obtained by the new algorithm achieve the expected fusion image effect under three different types of sunlight conditions.
- Is Part Of:
- International journal of computer applications technology. Volume 69:Number 1(2022)
- Journal:
- International journal of computer applications technology
- Issue:
- Volume 69:Number 1(2022)
- Issue Display:
- Volume 69, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 69
- Issue:
- 1
- Issue Sort Value:
- 2022-0069-0001-0000
- Page Start:
- 73
- Page End:
- 85
- Publication Date:
- 2022-10-06
- Subjects:
- binocular acquisition system -- ToF -- camera calibration -- image fusion
Technology -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.inderscience.com/jhome.php?jcode=ijcat ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 0952-8091
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23456.xml