Are MSER features really interesting?

Ron Kimmel, Cuiping Zhang, Alex Bronstein, Michael Bronstein

Research output: Contribution to journalArticlepeer-review


Detection and description of affine-invariant features is a cornerstone component in numerous computer vision applications. In this note, we analyze the notion of maximally stable extremal regions (MSERs) through the prism of the curvature scale space, and conclude that in its original definition, MSER prefers regular (round) regions. Arguing that interesting features in natural images usually have irregular shapes, we propose alternative definitions of MSER which are free of this bias, yet maintain their invariance properties.

Original languageEnglish
Article number5936074
Pages (from-to)2316-2320
Number of pages5
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number11
StatePublished - 2011


  • MSER
  • affine invariance
  • correspondence
  • feature detector
  • stable region

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


Dive into the research topics of 'Are MSER features really interesting?'. Together they form a unique fingerprint.

Cite this