Comparing the Use of Sum and Difference Histograms and Gray Levels Occurrence Matrix for Texture Descriptors
Adriel Santos Araujo, Aura Conci, Maira Beatriz Hernández Morán, Roger Resmini · 2018
Computation of texture information for image classification and pattern recognition is a highly complex activity. Much of this complexity is related to feature extractions where computational cost is related with the tonal levels and resolution of the images. One of the more used methods is the Gray Level Occurrence Matrix (GLCM) that present quadratic time complexity in relation to of gray levels. After the computation of such a matrix the Haralick descriptors are calculated from the GLCM and used for the next steps of classification for pattern recognition. However, the same descriptors can be calculated from another approach, with lower complexity and computational cost, presenting the same results as this work shows. This approach is based on the construction of the Sum and Difference Histograms (SDH). The computational complexity of this method is linear in relation to the amount of gray levels. This work, by examples, demonstrates the above mentioned statement.