Stream processing to solve image search by similarity


  • Jair Lobos LIDIC, Universidad Nacional de San Luis, San Luis, Argentina
  • Graciela Verónica Gil Costa LIDIC, Universidad Nacional de San Luis, San Luis, Argentina
  • Nora Susana Reyes LIDIC, Universidad Nacional de San Luis, San Luis, Argentina
  • Alicia Marcela Printista LIDIC, Universidad Nacional de San Luis, San Luis, Argentina
  • Mauricio Marín DIINF, Universidad de Santiago, Chile


stream processing, metrics spaces, MPEG-7, sparse spatial selection


The classic use of Stream Processing platforms enables working with data in real time, which allows you to generate data analysis quickly attending to a decisionmaking process. However, you can use these platforms for other applications such as indexing and subsequent use of similarity search objects in a database. The images can be displayed on a metric space, which has features that allow rules to discard a not similar image quickly without making costly computations. This paper presents the use of a Stream Processing platform to index images generated by different users. For this, it is necessary to represent these images by vectors containing different MPGE-7 features. This paper shows a Stream Processing platform using its processing elements (PEs) in parallel to speed up the operations involved in the index construction.


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How to Cite

Lobos, J., Gil Costa, G. V., Reyes, N. S., Printista, A. M., & Marín, M. (2015). Stream processing to solve image search by similarity. Journal of Computer Science and Technology, 15(02), p. 93–99. Retrieved from



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