Last ten years have witnessed the growth of many computer vision applications for food recognition. Dietary studies showed that dietary-related problem such as obesity is associated with other chronic diseases like hypertension, irregular blood sugar levels, and increased risk of heart attacks. The primary cause of these problems is poor lifestyle choices and unhealthy dietary habits, which are manageable by using interactive mHealth apps that use automatic visual-based methods to assess dietary intake. This review discusses the most performing methodologies that have been developed so far for automatic food recognition. First, we will present the rationale of visual-based methods for food recognition. The core of the paper is the presentation, discussion and evaluation of these methods on popular food image databases. We also discussed the mobile applications that are implementing these methods. The review ends with a discussion of research gaps and future challenges in this area.