Multi-Threshold Segmentation Using Genetic Algorithm
- Login to Download
- 1 Credits
Resource Overview
The adjustable count parameter determines the number of threshold values for segmentation
Detailed Documentation
In the count parameter, users can dynamically adjust the number of thresholds according to specific requirements. This implementation provides greater flexibility in controlling segmentation conditions through genetic algorithm optimization. The code typically involves defining the count parameter as an input variable that determines how many threshold levels the genetic algorithm will evolve, with fitness functions evaluating segmentation quality based on between-class variance or entropy criteria. This approach enables adaptive threshold selection for complex image segmentation scenarios where fixed single thresholds prove insufficient.
- Login to Download
- 1 Credits