Estimate freshness of chicken meat using image processing and artificial intelligent techniques

Document Type : Research Paper


1 Mechanical Engineering of Biosystems Department, Lorestan University, Khorramabad, Iran

2 university of Lorestan

3 Lorestan University


In the current study, new methods such as image processing and artificial intelligence have been used for the fast, easy and non-destructive evaluation of chicken meat freshness. After image acquisitions and pre-processing operations, the images were transferred to different color spaces and the statistical texture features of images were extracted. The feature selection operation was performed by combining particle swarm optimization (PSO) and artificial neural networks (ANNs) classifier to reduce the amount of calculations and improve the classification indicators. According to the number of selected features, the number of existing neurons in input layer were obtained 22 and the number of existing neurons in output layer were determined 5, according to classify the images as 5 classes. In the purpose of the classifier assessment operation to estimate the freshness of chicken meat, the statistical indicators such as precision, accuracy, sensitivity, specificity and area under the curve were calculated, which the values of these indicators for classification based on the selected features are 92, 80.02, 80.68, 94.89 and 87.83 percent, respectively. The obtained results of this study indicates that suggested system has the ability to diagnosis the chicken meat freshness with suitable accuracy.


Main Subjects

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