Abstract
BackgroundBeef quality measurement is a complex task with high economic impact. There is high interest in obtaining an automatic quality parameters estimation in live cattle or post mortem. In this paper we set out to obtain beef quality estimates from the analysis of ultrasound (in vivo) and color images (post mortem), with the measurement of various parameters related to tenderness and amount of meat: rib eye area, percentage of intramuscular fat and backfat thickness or subcutaneous fat.ProposalAn algorithm based on curve evolution is implemented to calculate the rib eye area. The backfat thickness is estimated from the profile of distances between two curves that limit the steak and the rib eye, previously detected. A model base in Support Vector Regression (SVR) is trained to estimate the intramuscular fat percentage. A series of features extracted on a region of interest, previously detected in both ultrasound and color images, were proposed. In all cases, a complete evaluation was performed with different databases including: color and ultrasound images acquired by a beef industry expert, intramuscular fat estimation obtained by an expert using a commercial software, and chemical analysis.ConclusionsThe proposed algorithms show good results to calculate the rib eye area and the backfat thickness measure and profile. They are also promising in predicting the percentage of intramuscular fat.
Highlights
Beef quality measurement is a complex task with high economic impact
The proposed algorithms show good results to calculate the rib eye area and the backfat thickness measure and profile. They are promising in predicting the percentage of intramuscular fat
In this work we propose a method based on curve evolution both for rib eye area and subcutaneous fat thickness measurements
Summary
In meat industry it is critical to have objective indicators that measure beef quantity and quality. In this work we propose a method based on curve evolution both for rib eye area and subcutaneous fat thickness measurements. In this work we present new methods to automatically measure three beef quality parameters, IMF% in ultrasound images, rib eye area and backfat thickness in color images in slaughtered steers. Since the rib eye is the biggest meat region present in the steak, the erosion is performed iteratively until only one connected component is present in the image that should belong to the interior of the rib eye The edges of this region defines the initial curve, that in the first stage of the curve evolution algorithm is evolved by considering only the role of the “high-contrasted” edges (Figure 13, 14, 15). Intramuscular fat percentage estimation Intramuscular fat percentage (IMF%) is the proportion of fat between the muscle fibers of the rib eye This quality measure can be performed in color images in slaughtered animals, and in ultrasound images in live animals.
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