Analyzing images containing multiple sparse patterns with neural networks

Rangachari Anand, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The problem of analyzing images containing multiple sparse overlapped patterns is addressed. This problem arises naturally when analyzing the composition of organic macromolecules using data gathered from their NMR spectra. Using a neural network approach, excellent results are obtained in using NMR data to analyze the presence of various amino acids in protein molecules. High correct classification percentages (about 87%) are achieved for images containing as many as five substantially distorted overlapping patterns.

Original languageEnglish (US)
Pages (from-to)1717-1724
Number of pages8
JournalPattern Recognition
Issue number11
StatePublished - Nov 1993


  • Clustering
  • Neural networks
  • Nuclear Magnetic Resonance
  • Overlapping patterns
  • Sparse image analysis

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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