Tolerance Near Sets and tNM Application in City Images

  • Deivid de Almeida Padilha da Silva
  • Daniel Caio de Lima
  • José Hiroki SaitoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11537)


The Tolerance Near Set theory - is a formal basis for the observation, comparison and classification of objects, and tolerance Nearness Measure (tNM) is a normalized value, that indicates how much two images are similar. This paper aims to present an application of the algorithm that performs the comparison of images based on the value of tNM, so that the similarities between the images are verified with respect to their characteristics, such as Gray Levels and texture attributes extracted using Gray Level Co-occurrence Matrix (GLCM). Images of the center of some selected cities around the world, are compared using tNM, and classified.


tNM Near Sets tolerance Near Sets Gray level Statistical attributes 



Deivid de Almeida Padilha da Silva acknowledges CAPES, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, the Brazilian Federal Government Agency under the Ministry of Education, for granting his Master Degree scholarship.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Deivid de Almeida Padilha da Silva
    • 1
  • Daniel Caio de Lima
    • 2
  • José Hiroki Saito
    • 1
    • 2
    Email author
  1. 1.UNIFACCAMP ? University Center of Campo Limpo PaulistaSão PauloBrazil
  2. 2.UFSCar - Federal University of São CarlosSão CarlosBrazil

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