内准确率达88%。The conventional manual methods for egg volume(V) and surface area(S) detection are usually slow, inefficient and not able to meet the actual production requirements, so machine vision technology was researched to replace them. Assumed the ideal egg image was symmetric about longitudinal diameter, the definition of volume pixel(Vp), surface areas pixel(Sp) and the calculation were proposed. Then, the module between volume (surface area) and Vp (Sp) was established. Experimental results showed that the determination coefficient of volume module and surface area was 0.965 and 0.971, respectively; the test accuracy of egg volume module and surface area reached 92% with ±1 cm3 error and 88% with ±1cm2 error respectively.
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周平,赵春江,王纪华,郑文刚,孙忠富,文友先.基于机器视觉的鸡蛋体积与表面积计算方法[J].农业机械学报,2010,41(5):168-171.Egg Geometry Calculations Based on Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(5):168-171