Spatial $$\alpha $$-Trimmed Fuzzy C-Means Algorithm to Image Segmentation
| Autor: | Manuel Mejía Lavalle, Virna V. Vela-Rincón, Dante Mújica-Vargas, Andrea Magadán Salazar |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology Image segmentation Filter (signal processing) Fuzzy logic Image (mathematics) Noise ComputingMethodologies_PATTERNRECOGNITION Outlier 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Segmentation Spatial analysis Algorithm |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030490751 MCPR |
| Popis: | An important aspect should be taken into account, when an image is segmented, the presence of atypical information. In this investigation an algorithm is proposed that is noise tolerant in the segmentation process. A method to image segmentation that combines Fuzzy C-Means (FCM) algorithm and Trimmed Means filter, called Spatial \(\alpha \) Trimmed Fuzzy C-means, using local information to achieve better segmentation. The FCM is very sensitive to noise, and the Trimmed Means filter is used to eliminate outliers with a lower computational cost. Compared to some state-of-the-art algorithms, the proposed is faster and noise tolerant, demonstrating better performance in the metrics considered. |
| Databáze: | OpenAIRE |
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