Speaker
Description
Otsu's Method is a widely used image segmentation technique designed to automatically determine the optimal threshold for separating objects from the background in a grayscale image. Developed by Nobuyuki Otsu in 1979, this algorithm aims to maximize the inter-class variance between foreground and background pixels while minimizing the intra-class variance within each region. The method efficiently identifies the threshold that best discriminates between object and non-object pixels by iteratively evaluating possible thresholds and calculating their associated variances. Once the optimal threshold is determined, the image is binarized, creating a clear distinction between the targeted objects and the background. Otsu's Method has proven robust and computationally efficient, making it a popular choice for applications such as medical image analysis, character recognition, and various computer vision tasks where precise segmentation is crucial for subsequent analysis and interpretation. Its simplicity and effectiveness contribute to its enduring relevance in diverse image processing domains.
| Presenting author | Ilina Mihai |
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