Abstract: The present disclosure provides a system and method for determining a nutritional value of a food item. The system and method utilizes a food container as a model to adjust various types of distortions that exists in an instant image of the food container that retains the food item. The instant image may be compared to the model image of the food container to correct any distortions. The food container includes a boundary which has a predetermined color. The predetermined color of the boundary can be used to adjust the color configuration of the instant image, thereby increasing the accuracy of the food identification.

Abstract: The present disclosure provides a system and method for determining a nutritional value of a food item. The system and method utilizes a food container as a model to adjust various types of distortions that exists in an instant image of the food container that retains the food item. The instant image may be compared to the model image of the food container to correct any distortions. The food container includes a boundary which has a predetermined color. The predetermined color of the boundary can be used to adjust the color configuration of the instant image, thereby increasing the accuracy of the food identification.

Abstract: The present disclosure provides a system and method for determining a nutritional value of a food item. The system and method utilizes a food container as a model to adjust various types of distortions that exists in an instant image of the food container that retains the food item. The instant image may be compared to the model image of the food container to correct any distortions. The food container includes a boundary which has a predetermined color. The predetermined color of the boundary can be used to adjust the color configuration of the instant image, thereby increasing the accuracy of the food identification.

Abstract: The invention relates to a novel method for automatically inspecting, e.g., aluminium cast parts using a monocular sequence of X-ray images taken of the test piece in different positions. Known methods for the automatic detection of casting defects use modified median filters which estimate X-ray images that are free of defects using recorded X-ray images. These images are compared with each other and casting defects are detected when a particularly great difference exists between them. However, the configuration of each filter depends to a considerable extent on the size, shape and position of the constructional structure of the test piece. These characteristics of the test piece therefore have to be considered a priori. The invention provides a method enabling casting defects to be automatically detected in two steps. The method uses a single filter and no a priori knowledge of the structure of the test piece.