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MSER: Maximally Stable Extremal Regions

MSER regions are connected areas with almost uniform intensity amidst contrasting backgrounds, identified through thresholding. These regions maintain consistent shapes across multiple thresholds. The process involves area function analysis to detect stable regions. Ellipse fitting and normalization are performed for improved features. Examples of MSER regions and construction methods are provided.

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MSER: Maximally Stable Extremal Regions

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  1. MSER Operator: Maximally Stable Extremal Regions • MSER regions are connected areas characterized • by almost uniform intensity, surrounded by contrasting • background. • They are constructed through a process of trying • multiple thresholds. • The selected regions are those that maintain • unchanged shapes over a large set of thresholds. Matas et al. 2001

  2. Examples of MSER Regions

  3. Another Example

  4. MSER Construction (1) intensity image shown as a surface function Watershed segmentation algorithms come from the concept of filling a basin with water to different levels.

  5. MSER Construction (2)

  6. MSER Computation (3) • For each threshold, compute the connected binary regions. • Compute a function, area A(i), at each threshold value i. • Analyze this function for each potential region to determine those that persist with similar function value over multiple thresholds.

  7. Analysis of Area Function

  8. Regions detected at different thresholds have different areas

  9. Normalization MSER regions Ellipse Fitting Ellipse Dilation

  10. Affine transformation from ellipses to circular regions plus intensity normalization

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