Abstract
This study detected image blobs and estimated parameters using the determinant of the Hessian operator. To investigate differential detectors quantitatively, a mathematical function was used to represent the blobs and to solve the parameters, including the position, width, length, contrast, offset, and orientation, in a closed form. These proposed parameters are both novel and very accurate. Sub-pixel localization and interpolation improved the accuracy. Noise is suppressed using the neighbors of the feature. This method was tested with various types of synthesized blobs and real-world images, and it detected fewer duplicated features. Experiments showed that the proposed method outperformed other methods.
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Xu, X. (2014). Blob Detection with the Determinant of the Hessian. In: Li, S., Liu, C., Wang, Y. (eds) Pattern Recognition. CCPR 2014. Communications in Computer and Information Science, vol 483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45646-0_8
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DOI: https://doi.org/10.1007/978-3-662-45646-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45645-3
Online ISBN: 978-3-662-45646-0
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