期刊名称：Journal of Emerging Trends in Computing and Information Sciences
电子版ISSN：2079-8407
出版年度：2013
卷号：4
期号：3
页码：257-262
出版社：ARPN Publishers
摘要：Automatic separation of defective eggs from qualified would lead to a great reduction on the graders visual stress as well as to an improvement on the quality control process. This paper presents image processing based non-destructive and cost-effective technique to detect various cracks, dirt in egg shell and internal blood spots. Cracks usually have low luminance and thus the bottom hat transform is used to extract the cracks from the luminance component of the image after YIQ transformation. For estimating the freshness of the egg, the acquired candled images are enhanced to detect the bloodspots and then the number of pixels labeled as blood spots are counted. The database consists of acquired images from eggs under different illumination condition. The results are presented to demonstrate the validity of the proposed visual process on a wide sample of both defective and non-defective eggs
