Development of a computer vision system and novel evaluation criteria to characterize color and appearance of rice

บทความในวารสาร

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Jinorose M., Prachayawarakorn S., Soponronnarit S.

ผู้เผยแพร่: Taylor and Francis Group

ปีที่เผยแพร่ (ค.ศ.): 2010

วารสาร: Drying Technology (0737-3937)

Volume number: 28

Issue number: 9

หน้าแรก: 1118

หน้าสุดท้าย: 1124

จำนวนหน้า: 7

นอก: 0737-3937

eISSN: 1532-2300

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956632039&doi=10.1080%2f07373937.2010.506174&partnerID=40&md5=cdbadfff7af2d331f073308c863b6faa

ภาษา: English-Great Britain (EN-GB)

ดูในเว็บของวิทยาศาสตร์ | ดูบนเว็บไซต์ของสำนักพิมพ์ | บทความในเว็บของวิทยาศาสตร์

บทคัดย่อ

Rice quality evaluation, both during and after drying, is traditionally performed by visual inspection. However, this is a tedious, time-consuming, and subjective task. More importantly, there is hardly any standard objective method to effectively evaluate the quality of rice. Proper inspection methods, which would allow a better control of the rice drying process, are thus in great demand. Image analysis has recently emerged as one of the most promising techniques for quality analysis of various food products, including rice. However, in order to successfully apply image analysis to rice quality evaluation, an appropriate means to characterize a rice kernel is first needed. This study aimed to develop effective but simple computer-vision algorithms along with novel evaluation criteria that could be used to simultaneously inspect various visual qualities of rice, including grain contour, size, and color in terms of various types of kernel damage, viz. undermilled, red, yellow, and chalky kernels. It was found that the developed algorithms could be used to assess some dimensional parameters such as the major axis, minor axis, and projected area of rice kernels effectively. Through the use of the multivariate discriminant analysis, it was found that the hue, saturation, and value (HSV) color space could be used to evaluate various kernel defects, including kernel discolorations and chalkiness, that are otherwise difficult to assess satisfactorily. ฉ 2010 Taylor & Francis Group, LLC.

คำสำคัญ

Color systems, Kernel discoloration, Multivariate discriminant analysis, Quality evaluation