articleJan 1, 2013Closed access

Image Texture Feature Extraction Using GLCM Approach

Abstract

Abstract- Feature Extraction is a method of capturing visual content of images for indexing & retrieval. Primitive or low level image features can be either general features, such as extraction of color, texture and shape or domain specific features. This paper presents an application of gray level co-occurrence matrix (GLCM) to extract second order statistical texture features for motion estimation of images. The Four features namely, Angular Second Moment, Correlation, Inverse Difference Moment, and Entropy are computed using Xilinx FPGA. The results show that these texture features have high discrimination accuracy, requires less computation time and hence efficiently used for real time Pattern…

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644
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FWCI
19.60
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100%
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Authors

3

Topics & keywords

Keywords
  • Artificial intelligence
  • Computer vision
  • Computer science
  • Feature extraction
  • Pattern recognition (psychology)
  • Gray level
  • Texture (cosmology)
  • Image texture
UN Sustainable Development Goals
  • Reduced inequalities
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