A new system for segmentation and recognition of scenery images

S. Kudo, M. Hagiwara

Research output: Contribution to conferencePaper

Abstract

This paper proposes a new system for segmentation and recognition of scenery images. Most of the conventional methods for image recognition are based on rules or pattern matching. It is true that they have high accuracy. However, the generalization ability is not sufficient and they require heuristic knowledge. In addition, these methods are used on the assumption that images are segmented appropriately. The proposed system alleviates these shortcomings by effective combination of K-mean-type algorithm [4], Back Propagation algorithm (BP) and Fuzzy Inference Neural Network (FINN) [8].

Original languageEnglish
Pages2548-2553
Number of pages6
Publication statusPublished - 2001 Jan 1
EventInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
Duration: 2001 Jul 152001 Jul 19

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'01)
CountryUnited States
CityWashington, DC
Period01/7/1501/7/19

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'A new system for segmentation and recognition of scenery images'. Together they form a unique fingerprint.

  • Cite this

    Kudo, S., & Hagiwara, M. (2001). A new system for segmentation and recognition of scenery images. 2548-2553. Paper presented at International Joint Conference on Neural Networks (IJCNN'01), Washington, DC, United States.