| Autor: |
manjula poojary, Srinivas Yarramalle |
| Rok vydání: |
2022 |
| DOI: |
10.21203/rs.3.rs-1735380/v1 |
| Popis: |
Image segmentation is one of the challenging task in the area of digital image processing. Many methods are available for undergoing segmentation among which clustering techniques are assumed to be more outstanding. In this article the Expectation Maximization (EM) based Gaussian Mixture Model (GMM) is considered for segmentation. In order to identify the feature this article proposes a new Grasshopper Optimization Algorithm (GOA) based approach for segmentation along with BGMM and EM algorithm. The results are carried out on benchmark dataset namely UCI for medical images and aura images from Bio-well data sets. The results are evaluated using image quality metrics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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