Fuzzy logic-based disparity selection using multiple data costs for stereo correspondence
| Autor: | Raviraj Shetty, C. Gurudas Nayak, Akhil Appu Shetty, V I George |
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| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Cross-correlation Pixel Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Function (mathematics) Mutual information Fuzzy logic Stereopsis Benchmark (computing) Computer vision Artificial intelligence Electrical and Electronic Engineering business Selection (genetic algorithm) |
| Zdroj: | TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 27:377-391 |
| ISSN: | 1303-6203 |
| Popis: | Stereo matching algorithms are capable of generating depth maps from two images of the same scene taken simultaneously from two different viewpoints. Traditionally, a single cost function is used to calculate the disparity between corresponding pixels in the left and right images. In the present research, we have considered a combination of simple data costs. A new method to combine multiple data costs is presented and a fuzzy-based disparity selection method is proposed. Experiments with different combinations of parameters are conducted and compared through the Middlebury and Kitti Stereo Vision Benchmark. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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