基于小波变换的稻米爆腰检测技术研究

Detection of crack in brown rice kernel using wavelet transform

稻谷裂纹(俗称爆腰)是导致大米在加工过程中破碎的重要原因,爆腰的检测对裂纹的研究和控制有重要意义。本文提出了一种新的爆腰检测方法。它利用小波变换在图像边缘提取和去噪中的优越性,通过对二进尺度下图像小波变换局部极大值的检测,提取边缘特征,去除噪声,对糙米爆腰图像中的裂纹进行了有效识别。从而实现爆腰率的自动检测,准确率达到92%以上。与传统的检测算子相比,取得了更为良好的效果。

Ratio of intact kernel among rice sample is an important index when grading rice in market. Crack in brown rice kernel is the major factor to produc broken kernel during rice milling. A new method using wavelet transform to detect crack in brown rice kernel was described. Images of brown rice kernels were taken with new developed illumination style. The wavelet transform was applied to rice kernel image on binary scale. Edge feature of brown rice kernel was extracted while noise of image was smoothed. The partial maximum of wavelet transform was extracted and subsequently crack in brown rice kernel was detected effectively. Experiments showed that accuracy of crack identification is more than 92% and the new method is more satisfactory than classical differential operators.