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Automatic grading of Bi-colored apples by multispectral machine vision - ScienceDirect
Source: sciencedirect.com
Article summary:
1. Machine vision systems are widely used in the food industry, including for apple fruit inspection.
2. Grading bi-colored apples is more difficult due to color transition areas, but various machine vision techniques have been proposed for this task.
3. The proposed solution in this paper uses multispectral machine vision to segment defective skin and extract image features for statistical and syntactical classification into corresponding quality categories.
Article analysis:
该文章介绍了一种利用多光谱机器视觉自动对双色苹果进行分级的方法。然而，该文章存在以下问题：
1. 偏见来源：文章没有提及其他可能的方法或技术来解决苹果分级问题，只关注使用机器视觉的方法。
2. 片面报道：文章只介绍了使用机器视觉进行苹果分级的相关研究，但并未探讨其他可能的方法或技术。
3. 缺失考虑点：文章没有考虑到可能存在的误判率或错误分类率，并未探讨如何减少这些风险。
4. 主张缺失证据：文章提出了一种新的多类别分级方法，但并未提供足够的证据来支持其有效性和准确性。
5. 未探索反驳：文章没有探讨可能存在的反驳意见或争议，并未平等地呈现双方观点。
6. 宣传内容：文章过于宣传使用机器视觉进行苹果分级的优势和可行性，而忽略了其他可能存在的问题和挑战。
Topics for further research:
Alternative methods for apple grading
Exploring other approaches for apple grading
Addressing the issue of misclassification or error rates
Providing evidence for the effectiveness and accuracy of the proposed method
Considering potential counterarguments or controversies
Acknowledging challenges and limitations of using machine vision for apple grading