A new region-primitive method for classification of colour meat image texture based on size, orientation, and contrast

Abstract

A new structural method was developed to characterise texture of colour meat images. Structural primitives or region-primitives were constructed using a region-growing method with a global and automatically calculated threshold. A total of eight textural features under the consideration of size, orientation, and contrast, which are the primary factors of human perception of texture pattern, were obtained from the region-primitives. An experiment was set up to classify the texture pattern of a set of 60 cooked meat colour images consisting of 20 beef images, 20 lamb images, and 20 pork images using texture features obtained from the proposed region-primitive method and run-length matrix method, respectively. The proposed region-primitive method (error rate: 18.3%) was found to perform better than the run-length matrix method (error rate: 35.0%). Results also indicated that the texture features obtained by the proposed method carried adequate texture information for classification and that the proposed region-primitive method could be potentially used for the characterisation of irregular textural pattern in cooked meat images, which was inapproachable by conventional structural texture analysis techniques.