Food has a direct impact on an individual's life and is a significant area for the research community. Computational techniques in food-related computing are performed to address various food-related issues in the field of agronomy, medicine, biology etc. In this paper, we present a comprehensive review of research exclusively on segmentation techniques used for food computing. This paper illustrates the viable segmentation techniques used for food image segmentation. It also provides a comprehensive review of the same. A relevant survey on 66 research papers has been done to provide different food image segmentation techniques. A comparative study among these techniques is also done based on different parameters like type of algorithm, segmentation technique, dataset, and accuracy. Moreover, this paper focuses on research challenges in food recognition. Also a framework has been proposed in this paper to overcome the problem of watershed and OTSU algorithm.

食物对个人的生活有直接影响，是研究界的重要领域。在食品相关计算中使用计算技术来解决农学，医学，生物学等领域中与食品相关的各种问题。在本文中，我们将对仅用于食品计算的分割技术进行全面的研究。本文说明了用于食品图像分割的可行分割技术。它还提供了相同的全面审查。已经对66篇研究论文进行了相关调查，以提供不同的食物图像分割技术。还根据不同的参数（例如算法类型，分割技术，数据集和准确性）对这些技术进行了比较研究。而且，本文着重研究食品识别中的研究挑战。本文还提出了一个框架来克服分水岭和OTSU算法的问题。