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基于软X射线成像技术的柑橘内部浮皮和枯水检测
Detection of Peel Puffing and Granulation in Citrus Based on Soft X-ray Imaging Technology
针对传统方法无法高效、无损地对柑橘浮皮和枯水进行检测的问题,本研究自制了一套软X射线成像系统,包括载物传送装置、软X射线成像装置、触发装置和软X射线防护装置。本研究根据宽皮柑橘物理特性确定检测参数,以柑橘图像的清晰度、对比度、畸变率为评判标准,通过调节成像装置参数,确定了最佳的成像参数为:X射线源的管电压60 kV,管电流1.3 mA,线阵探测器的积分时间5.5 ms,柑橘输送带的传送速度10 cm/s。通过圆孔金属板对列方向畸变进行检测,结果表明,传送速度稳定,列方向畸变可以忽略;利用70 mm不锈钢标定球对行方向上的畸变进行检测,计算了行方向上不同位置的投影畸变系数,并建立了畸变校正模型。在上述参数下采集柑橘的软X射线图像,采用高斯滤波对柑橘图像进行去噪处理;利用图像增强算法对去噪后的图像进行对比度增强处理;将固定阈值分割法和形态学算法融合,以去除柑橘图像背景区域、分离柑橘果肉区域和果皮区域。最后通过面积百分比法计算柑橘果肉面积和柑橘果实面积比判别柑橘内部浮皮程度;提取柑橘果实区域的灰度特征,获取柑橘枯水区域,计算柑橘枯水面积和柑橘果肉面积比,判别柑橘枯水程度。以清江椪柑为实验对象,结果表明自制软X射线成像装置对清江椪柑的浮皮和枯水的总体识别率分别为96.2%和86.9%。说明本研究提出的方法能够实现柑橘内部浮皮和枯水的无损检测。
The internal quality of citrus is an important index for citrus grading, and the most common factors affecting the internal quality of citrus are peel puffing and granulation, which affect the fruit quality and lose the market value due to the large consumption of nutrients. In this study, a soft X-ray imaging device was developed, including a transmission device, a soft X-ray imaging device, a trigger device and a soft X-ray protection device, for the problem that traditional methods cannot detect citrus peel puffing and granulation efficiently and non-destructively. In this research, the detection parameters were determined according to the physical characteristics of wide peeled citrus, and the clarity, contrast and aberration rate of citrus images were used as the judging criteria. The best imaging parameters were determined by adjusting the parameters of the imaging device as follows: The tube voltage of X-ray source was 60 kV, the tube current was 1.3 mA, the integration time of line array detector was 5.5 ms, and the transmission speed of citrus conveyor belt was 10 cm/s. The aberrations in the column direction were detected by the circular hole metal plate, and the results showed that the transmission speed was stable and the aberrations in the column direction were negligible. The aberrations in the row direction ware detected by using the 70 mm stainless steel calibration sphere, and the projection aberration coefficients at different positions in the row direction were calculated, and the aberration correction model was established. The soft X-ray images of citrus were acquired under the above parameters, and Gaussian filtering was used to denoise the citrus images. The image enhancement algorithm was used to enhance the contrast of the denoised images. The fixed threshold segmentation method and morphological algorithm were fused to remove the background area, separate the flesh area and the peel area of the citrus images. Finally, the area percentage method was used to calculate the ratio of citrus flesh area to citrus fruit area to discriminate the degree of citrus peel puffing; the grayscale features of citrus fruit area were extracted to obtain the citrus withered area, and the ratio of citrus withered area to citrus flesh area was calculated to discriminate the degree of citrus granulation. Qingjiang Ponkan were taken as the experimental object, and the results showed that the overall recognition rate of the homemade soft X-ray imaging device were 96.2% and 86.9% for the peel puffing and granulation of Qingjiang Ponkan, respectively. The method proposed in this study may achieve nondestructive detection of peel puffing and granulation inside citrus.
软X射线成像 / 柑橘 / 图像处理 / 浮皮 / 枯水 / 检测 {{custom_keyword}} /
soft X-ray imaging / citrus / image processing / peel puffing / granulation / detection {{custom_keyword}} /
表 1 柑橘浮皮和枯水检测软X射线成像装置参数Table 1 Citrus peel puffing and granulation detection soft X-ray imaging device parameters |
装置参数 | 数值 |
---|---|
软X射线源管电压/kV | 60 |
管电流/mA | 1.3 |
线阵探测器积分时间/ms | 5.5 |
图像高度/px | 1024 |
抓取模式 | 帧抓取 |
扫描方向 | 垂直扫描 |
输送速度/(cm·s-1) | 10 |
表2 基于软X射线的柑橘浮皮和枯水检测不同滤波方法去噪后的图像MSE和PSNR值Table 2 MSE and PSNR values of images after denoising by different filtering methods for soft X-ray based citrus peel puffing and granulation detection |
滤波 方法 | 高斯滤波 | 均值滤波 | 中值滤波 | ||||||
---|---|---|---|---|---|---|---|---|---|
核大小 | 3×3 | 5×5 | 7×7 | 3×3 | 5×5 | 7×7 | 3×3 | 5×5 | 7×7 |
MSE | 2 | 4 | 12 | 4 | 14 | 31 | 10 | 25 | 52 |
PSNR | 45.12 | 42.11 | 37.34 | 42.11 | 36.67 | 33.22 | 38.13 | 34.15 | 30.97 |
表3 软X射线成像系统像素精度Table 3 Pixel accuracy of soft X-ray image system |
标定对象 | 像素尺寸/px | 实际尺寸/mm | 像素精度/(mm·px-1) |
---|---|---|---|
1 | 173 | 60 | 0.346 |
2 | 200 | 70 | 0.350 |
3 | 231 | 80 | 0.346 |
表4 柑橘浮皮程度分级Table 4 Classification of peel puffing citrus |
果肉区域面积百分比/% | 浮皮等级 | 特征描述 |
---|---|---|
(70,—) | 1级(健康果) | 囊瓣膜与果皮、果皮与囊衣无空隙症状 |
(60,70] | 2级(轻微浮皮) | 囊瓣与果皮、果皮与囊衣分离,未扩散整个果肉 |
(—,60] | 3级(重度浮皮) | 囊瓣与果皮、果皮与囊衣完全分离 |
表 5 柑橘枯水程度分级Table 5 Classification of citrus granulation |
枯水区域面积百分比/% | 枯水等级 | 特征描述 |
---|---|---|
0 | 1级(健康果) | 果皮正常,皮肉紧贴,汁胞正常,果汁丰满 |
(0,25) | 2级(轻微枯水) | 囊瓣略有皱缩,橙色变淡,少数汁胞呈轻微枯水 |
[25,50] | 3级(中度枯水) | 囊瓣皱缩,皮出现白色小点,囊瓣内有50%汁胞枯水 |
(50,—) | 4级(重度枯水) | 囊瓣明显皱缩,皮上有白斑,囊瓣和汁胞大部分枯水 |
表6 基于软X射线成像技术的柑橘内部浮皮检测结果Table 6 Results of peel puffing detection in citrus based on soft X-ray imaging |
果实大 小/mm | 调查果数/个 | 浮皮程度 | 准确检测数/个 | 准确率/% | ||
---|---|---|---|---|---|---|
无/个 | 轻/个 | 重/个 | ||||
S(60~65) | 130 | 127 | 3 | 0 | 279 | 96.2 |
M(65~70) | 70 | 61 | 7 | 2 | ||
L(70~80) | 90 | 44 | 35 | 11 |
表7 基于软X射线成像技术的柑橘内部枯水检测结果Table 7 Results of granulation detection in citrus based on soft X-ray imaging |
果实大 小/mm | 调查果数/个 | 枯水程度 | 准确检测数/个 | 准确率/% | |||
---|---|---|---|---|---|---|---|
无/个 | 轻/个 | 中/个 | 重/个 | ||||
S(60~65) | 130 | 122 | 8 | 0 | 0 | 252 | 86.9 |
M(65~70) | 70 | 55 | 11 | 4 | 0 | ||
L(70~80) | 90 | 54 | 20 | 12 | 4 |
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