Detection of individual specimens in populations using contour energies


Abstract:

In this paper we study how shape information encoded in contour energy components values can be used for detection of microscopic organisms in population images. We proposed features based on shape and geometrical statistical data obtained from samples of optimized contour lines integrated in the framework of Bayesian inference for recognition of individual specimens. Compared with common geometric features the results show that patterns present in the image allow better detection of a considerable amount of individuals even in cluttered regions when sufficient shape information is retained. Therefore providing an alternative to building a specific shape model or imposing specific constrains on the interaction of overlapping objects. © Springer-Verlag Berlin Heidelberg 2007.

Año de publicación:

2007

Keywords:

  • Feature Extraction
  • Statistical shape analysis
  • recognition

Fuente:

googlegoogle
rraaerraae
scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Visión por computadora
  • Optimización matemática

Áreas temáticas:

  • Métodos informáticos especiales