Infant pain recognition system with GLCM features and GANN under unstructed lighting condition

This paper discussed the crucial demand regarding the scheme to translate the silence voice from the newborn. The infant can´t afford to express their feeling of pain by voice. Hence, we proudly present an infant pain recognition system to overcome this matter. We employed the Single Scale Retinex (SSR) to remove the illumination level. Secondly, Gray-Level Co-occurrence Matrix (GLCM) was adopted as the feature extraction. We determine the condition of the infants (pain/no pain) with Hybrid Genetic Algorithm Neural Network (GANN) and Linear Discriminant Analysis (LDA). Several examples were conducted to evaluate the performance of the proposed method under different illumination levels.