title: Automatic segmentation of beef longissimus dorsi muscle and marbling by an adaptable algorithm.
abstract: An algorithm for automatic segmentation of beef longissimus dorsi (LD) muscle and marbling has been developed. The algorithm used simple thresholding to remove the background and then used clustering and thresholding with contrast enhancement via a customised greyscale to remove marbling. It was possible to attain lean muscle free of obvious marbling or background pixels where specular reflection could be effectively mitigated. Features of the automatically derived LD muscle and marbling images were compared to corresponding features of LD muscle and marbling images derived with a segmentation method requiring manual completion. Very strong correlations (up to r=1) were found between the colour features of both sets of LD muscle images. Strong correlations (up to r=0.96) were found between the features of both sets of marbling images. The automatic segmentation method has shown its good ability to approximate colour and marbling features. The algorithm has adaptable parameters and can be retailored to suit different image acquisition environments.
authors.affiliation: FRCFT Research Group, Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture and Food Science Centre, Belfield, Dublin 4, Ireland; Ashtown Food Research Centre, Teagasc, Ashtown, Dublin 15, Ireland.
authors.forename: Patrick
authors.initials: P
authors.lastname: Jackman
authors.forename: Da-Wen
authors.initials: DW
authors.lastname: Sun
authors.forename: Paul
authors.initials: P
authors.lastname: Allen