Research on Fundus Image Mosaic Method Based on Genetic Algorithm. (30th November 2021)
- Record Type:
- Journal Article
- Title:
- Research on Fundus Image Mosaic Method Based on Genetic Algorithm. (30th November 2021)
- Main Title:
- Research on Fundus Image Mosaic Method Based on Genetic Algorithm
- Authors:
- Wang, Shuang
- Other Names:
- Li Qiangyi Academic Editor.
- Abstract:
- Abstract : Retinal image mosaic is the key to detect common diseases, and the existing image mosaic methods are difficult to solve the problems of low contrast of fundus images and geometric distortion between images in different fields of view. To solve the problem of noise in retinal fundus images, an image mosaic algorithm based on the genetic algorithm was proposed. Firstly, a series of morphological pretreatment was performed on the fundus images. Then, the vascular network is extracted by obtaining the maximum entropy of the image to determine the threshold value. The similarity of the image to be spliced is a feature, and the genetic algorithm is used to solve the optimal parameters to achieve the maximum similarity. By smoothing the image, a clear image with minimum noise is obtained. Experimental results show that the proposed algorithm can effectively realize the image mosaic of the fundus. The method proposed in this paper can provide support for high-precision automatic stitching of multiple single-mode color fundus images.
- Is Part Of:
- Advances in multimedia. Volume 2021(2021)
- Journal:
- Advances in multimedia
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11-30
- Subjects:
- Multimedia systems -- Periodicals
Computer networks -- Periodicals
Multimédia
Réseaux d'ordinateurs
Computer networks
Multimedia systems
Periodicals
006.7 - Journal URLs:
- https://www.hindawi.com/journals/am/ ↗
http://bibpurl.oclc.org/web/22854 ↗ - DOI:
- 10.1155/2021/6060691 ↗
- Languages:
- English
- ISSNs:
- 1687-5680
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 20207.xml