Name
Title | ||
|---|---|---|
Colour image segmentation with histogram and homogeneity histogram difference using evolutionary algorithms |
Abstract | ||
|---|---|---|
Due to the complexity of underlying data in a color image, retrieval of specific object features and relevant information becomes a complex task. Colour images have different color components and a variety of colour intensity which makes segmentation very challenging. In this paper we suggest a fitness function based on pixel-by-pixel values and optimize these values through evolutionary algorithms like differential evolution (DE), particle swarm optimization (PSO) and genetic algorithms (GA). The corresponding variants are termed GA-SA, PSO-SA and DE-SA; where SA stands for Segmentation Algorithm. Experimental results show that DE performed better in comparison of PSO and GA on the basis of computational time and quality of segmented image. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s13042-015-0360-7 | Int. J. Machine Learning & Cybernetics |
Keywords | Field | DocType |
Segmentation, Evolutionary algorithms, Colour image, Homogeneity | Histogram,Computer vision,Scale-space segmentation,Pattern recognition,Evolutionary algorithm,Segmentation-based object categorization,Fitness function,Image segmentation,Artificial intelligence,Region growing,Mathematics,Color image | Journal |
Volume | Issue | ISSN |
9 | 1 | 1868-808X |
Citations | PageRank | References |
7 | 0.44 | 42 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sushil Kumar | 1 | 510 | 54.39 |
| Millie Pant | 2 | 320 | 32.47 |
| Manoj Kumar | 3 | 732 | 104.98 |
| aditya dutt | 4 | 7 | 0.44 |