1. AN OTSU image segmentation based on fruitfly optimization algorithm
- Author
-
Yunliang Wen, Xiaorui Li, and Chunyan Huang
- Subjects
Image segmentation ,Optimization algorithm ,business.industry ,Computer science ,020209 energy ,Threshold ,Evaluation index ,General Engineering ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,OTSU ,Pattern recognition ,02 engineering and technology ,Fruit fly optimization algorithm (FOA) ,Engineering (General). Civil engineering (General) ,01 natural sciences ,010305 fluids & plasmas ,Simplicity (photography) ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,Segmentation ,Artificial intelligence ,TA1-2040 ,business - Abstract
Despite its simplicity and high accuracy, the real-time efficiency of OTSU segmentation is not high. In order to promote the real-timeliness of image segmentation, this paper introduces the fruitfly optimization algorithm (FOA) to OTSU segmentation, creating an FOA-OTSU segmentation algorithm. In the proposed algorithm, the optimal threshold for segmentation is searched for by the FOA. The classic Lena picture, Flower picture and Cameraman picture were used for simulation experiment, and the results were evaluated by signal-to-noise ratio (SNR) and peak signal-to-noise ratio (PSNR). The results show that the segmentation time is reduced by about 50.0% on the premise of the PSNR and SNR evaluation criteria and the segmentation effect basically unchanged. The simulations indicate that our method converges faster and consumes fewer time than traditional OTSU algorithm, without sacrificing the segmentation accuracy. The research provides a desirable tool with high real-time performance of rapid image segmentation.
- Published
- 2021