Method and Device for Bone Scan in Meat

Abstract

A method and device for detection of bone in meat identifies fragments larger than about 1 mm using spectral optical imaging and ultrasound. Spectral imaging can detect foreign material proximate to the surface and ultrasound can detect material within the sample. The sample is irradiated by light and reflected light or Raman scattered light measured. The sample is similarly irradiated by ultrasound and reflected or transmitted sound waves give a set of amplitude data points, which include temporal delay. These data points are then processed by statistical methods to derive a set of vectors in n-dimensional space, which are compared to a calibrated data set of derived vectors which have distinct identifying loci for each type of surface, are indicative of the presence or absence of defects.

Description

FIELD OF THE INVENTION[0001]The present invention pertains to the detection of small objects wholly or partly embedded in soft tissue. Generally, although not essentially, the objects are bone fragments or very small bones in meat. Large bones are not a problem because they are easily visible. Commercially, most typically, the meat is chicken breast, as the bone tends to fragment when the breast is deboned. The invention can also be applied to poultry, fish, and other meats liable to contain bone fragments or very small bones.BACKGROUND OF THE INVENTION[0002]Bone fragments or hard objects larger than 1 mm in size, which may be present in food products, pose a risk to human health. Consequently bone fragments pose both a regulatory risk and a litigation risk to food processing operations. For a bone detection method to be commercially viable, the method must be able to reliably detect bone fragments at the small end of the range. Surface defects are more common, embedded defects less...

AI Technical Summary

Benefits of technology

[0104]The advantage of the system is that it detects both surface and embedded bone in chicken breast. Although the surface of a food sample may be quite irregular on a large scale, the surface normally does not vary much on a scale of a few millimeters so the illumination and mean angle of reflection are nearly constant. Within this approximation, changes in the gradient of reflected intensity exceeding a threshold are indicative of a change in composition and can be used to detect edges. Edge detection is well known, and off the shelf processing software is commercially available. Once an edge is detected, the algorithm searches for other nearby edges and calculates a defect probability based on the magnitude of the gradient, the length of the edge, and the mutual geometry all edges within an analysis region. As an illustrative example, bones often have edges that are nearly parallel with a characteristic spacing between edges. The detection of parallel edges several mm long approximately 2 mm apart in chicken flesh would cause the algorithm to generate a

Problems solved by technology

Bone fragments or hard objects larger than 1 mm in size, which may be present in food products, pose a risk to human health.

Consequently bone fragments pose both a regulatory risk and a litigation risk to food processing operations.

Other biomolecules are present, but not in sufficient quantity to have a significant effect on the types of measurements discussed herein.

The technical problem is to find bone in a meat matrix composed of protein and lipid.

The primary weakness of this method is that tissue scatters photons at every refractive index discontinuity, effectively on the scale of cellular dimensions.

The candling method is thus limited to thin samples with uniform thickness.

Secondly, the signal from a small de

Images