Lu Yuzhen, Sardari Hamed
Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA.
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.
Data Brief. 2025 May 6;60:111612. doi: 10.1016/j.dib.2025.111612. eCollection 2025 Jun.
Wood breast (WB) myopathy is an economically important muscular defect that downgrades poultry meat quality and currently requires manual assessment for identifying and removing affected products at processing lines. An image dataset was created to assess WB conditions in broiler breast fillets using structured-illumination reflectance imaging (SIRI) as a non-destructive, objective means for WB assessment. A custom-assembled SIRI platform was used for sample imaging, and it mainly consisted of a broadband quartz tungsten halogen light source, a digital micro-mirror-device-based projector that shined phase-shifted sinusoidal patterns of light over samples, a monochromatic camera with a resolution of 2048 × 2048 pixels, and a computer, operating in an enclosed chamber. A total of 168 broiler breast fillets were collected from a commercial poultry processing plant and categorized by trained personnel into 72 "Normal" (WB-free) and 96 "Defective" (WB-affected) fillets based on tactile palpation and visual inspection. Sinusoidal illumination patterns at eight different spatial frequencies (0.015-0.150 cycles/mm) were sequentially projected onto the samples, and the reflectance pattern images were captured under the sinusoidal illumination of three phase-shifted patterns at each spatial frequency, yielding a set of 24 images acquired per sample. Hence the dataset consists of a total of 4032 raw pattern images, each of which is of size 2048 × 2048 pixels and saved as a 16-bit grayscale image in .tif format. Through demodulation, direct component (DC), amplitude component (AC), and phase difference images can be readily obtained from the three phase-shifted raw pattern images at each spatial frequency, and these images, especially the phase difference image that depicts the surface geometry, are useful for WB assessment and sample classification. In addition to the raw pattern images, the demodulated image (DC, AC, and phase difference) data is also included in the dataset. This dataset represents the first publicly available SIRI dataset and is expected to be a valuable resource for advancing SIRI for poultry quality assessment and beyond.
木鸡胸（WB）肌病是一种在经济上具有重要影响的肌肉缺陷，它会降低禽肉品质，目前在加工生产线中需要通过人工评估来识别和剔除受影响的产品。创建了一个图像数据集，使用结构光反射成像（SIRI）作为一种非破坏性的、客观的手段来评估肉鸡胸脯肉中的WB状况。一个定制组装的SIRI平台用于样本成像，它主要由一个宽带石英卤钨光源、一个基于数字微镜器件的投影仪（该投影仪将相移正弦光图案投射到样本上）、一个分辨率为2048×2048像素的单色相机以及一台在封闭腔室内运行的计算机组成。从一家商业家禽加工厂收集了总共168块肉鸡胸脯肉，经过训练有素的人员根据触觉触诊和目视检查，将其分为72块“正常”（无WB）和96块“有缺陷”（受WB影响）的胸脯肉。八个不同空间频率（0.015 - 0.150周期/毫米）的正弦照明图案依次投射到样本上，并且在每个空间频率下，在三个相移图案的正弦照明下捕获反射图案图像，每个样本获取一组24张图像。因此，该数据集总共包含4032张原始图案图像，每张图像大小为2048×2048像素，并以16位灰度图像的形式保存为.tif格式。通过解调，可以从每个空间频率下的三个相移原始图案图像中轻松获得直流分量（DC）、幅度分量（AC）和相位差图像，这些图像，特别是描绘表面几何形状的相位差图像，对于WB评估和样本分类很有用。除了原始图案图像外，解调后的图像（DC、AC和相位差）数据也包含在数据集中。这个数据集是第一个公开可用的SIRI数据集，预计将成为推进SIRI用于家禽质量评估及其他领域的宝贵资源。
