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Bone Fragment Detection in Chicken Breast Fillets Using Transmittance Image Enhancement

机译:利用透射图像增强技术检测鸡胸肉骨碎片

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摘要

This article is concerned with the detection of bone fragments embedded in de-boned skinless chicken breast fillets by modeling optical images generated by backlighting. Imaging of chicken fillets is often dominated by multiple scattering properties of the fillets. Thus, resulting images from multiple scattering are diffused, scattered, and low contrast. In this study, a combination of transmittance and reflectance hyperspectral imaging, which is a non-ionized and non-destructive imaging modality, was investigated as an alternative method to conventional transmittance x-ray imaging, which is an ionizing imaging modality. As a way of reducing the influence of light scattering on images and thus increasing the image contrast, the use of a structured line light was examined along with an image formation model that separated undesirable lighting effects from an image. The image formation model, based on an illumination-transmittance model, was applied for correcting non-uniform illumination effects so that embedded bones were more easily detected by a single threshold. An automated image processing algorithm to detect bones was also proposed. Experimental results with chicken breast fillets and bone fragments are provided. The detection accuracy of the developed technology was 100%. The false-positive rate was 10%.
机译:本文涉及通过对由背光产生的光学图像进行建模来检测嵌入去骨去皮去皮鸡胸肉鱼片中的骨碎片。鸡柳的成像通常由鱼柳的多种散射特性决定。因此,由多次散射产生的图像被散射,散射并且对比度低。在这项研究中,作为非电离和非破坏性成像方式的透射率和反射率高光谱成像的组合,被研究作为传统透射率X射线成像(电离成像方式)的替代方法。作为减少光散射对图像的影响并因此提高图像对比度的一种方法,研究了结构化线光的使用以及将不需要的照明效果与图像分开的图像形成模型。应用基于光照透射率模型的图像形成模型来校正不均匀的光照效果,以便通过单个阈值更容易检测到嵌入的骨骼。还提出了一种自动图像处理算法来检测骨骼。提供了鸡胸肉鱼片和骨头碎片的实验结果。所开发技术的检测精度为100%。假阳性率为10%。

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