Image Transform based on Alpha-Beta Associative Memories

Authors

  • Antonio Alarcón Paredes Centro de Investigación en Computación, Instituto Politécnico Nacional.
  • Oleksiy Pogrebnyak Centro de Investigación en Computación, Instituto Politécnico Nacional.
  • Amadeo José Argüelles Cruz Centro de Investigación en Computación, Instituto Politécnico Nacional.

DOI:

https://doi.org/10.13053/cys-17-4-184

Keywords:

Transform methods, pattern recognition, image processing, associative memories, compression.

Abstract

In this paper, a new method of alpha-beta associative memories for images (MAABI) is presented. This method results in the alpha-beta transform (TAB) for images. The alpha-beta transform presented in this paper is applied to sub-blocks of a gray-scale image and generates an alpha-beta heteroassociative memory on each sub-block using a given transformation matrix. By means of the inverse alpha-beta transform (TABI), the original image patterns are recovered. The data compression process is divided into three stages: transformation, quantization and coding. Our model is focused on image transformation; we compare it with the morphological transform (TM) based on the morphological associative memories (MAM). In order to measure the number of bits contained in an image, the Shannon's entropy is used. The TM, as well as such traditional transforming methods as the discrete cosine transform (DCT) and the discrete wavelet transform (DWT), cannot perform compression over an image; that is why the main advantage of the AB is a smaller value of the entropy measure of the transformed image compared to the entropy of the original image. In addition, TAB provides a faster processing with a small number of elementary operations such as addition, subtraction, maximum and minimum.

Author Biographies

Antonio Alarcón Paredes, Centro de Investigación en Computación, Instituto Politécnico Nacional.

Recibió el grado de Maestro en Ciencias en Ingeniería de Cómputo, en 2009, por el Centro de Investigación en Computación del Instituto Politécnico Nacional; donde actualmente se encuentra realizando estudios de Doctorado en Ciencias de la Computación. Sus áreas de interés son: memorias asociativas, reconocimiento de patrones y procesamiento/compresión de imágenes.

Oleksiy Pogrebnyak, Centro de Investigación en Computación, Instituto Politécnico Nacional.

Doctor en Ciencias en Sistemas Radiotécnicos, por el Instituto de Aviación de Kharkov (ahora Universidad Nacional Aeroespacial), Ucrania, en 1991. Actualmente, trabaja en el Centro de Investigación en Computación del Instituto Politécnico Nacional, Mexico. Sus áreas de interés incluyen el filtrado y compresión de imágenes/señales digitales y percepción remota.

Amadeo José Argüelles Cruz, Centro de Investigación en Computación, Instituto Politécnico Nacional.

Doctor en Ciencias de la Computación por el Centro de Investigación en Computación, del Instituto Politécnico Nacional, en 2007. Sus áreas de interés son redes neuronales sin pesos, memorias asociativas, reconocimiento de patrones.

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Published

2013-12-30

Issue

Vol. 17 No. 4 (2013): 17(4) October-December 2013

Section

Articles

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