Fluoroscopic inspection method, device and storage medium for automatic classification and recognition of cargoes

A fluoroscopic inspection device for automatic classification and recognition of cargoes, comprising:

• a processor,
• a memory, configured to store instructions executable by the processor,
• wherein the processor is configured to:
• perform scanning and imaging for a container by using an X-ray scanning device to acquire a scanned image;
• segment the scanned image into small regions according to gray scales and texture features, with the gray scale and the texture feature of the image are uniform in each small region;
• extract features of the small regions;
• generate a classifier according to annotated images, and/or store or update an existing classifier;
• and
• recognize the small regions by using the classifier according to the extracted features, to obtain a probability of each small region pertaining to a certain category of cargoes, and merge small regions to obtain large regions each representing a category,
• wherein the automatic classification and recognition performed by the processor of the device for the cargoes comprises a training stage, and
• wherein, in the training stage,
• firstly, after scanned images of cargoes in containers are acquired, each of the scanned images is pre-segmented into small regions according to similarities in terms of gray scales and texture features, and features of the small regions are extracted;
• subsequently, each of the scanned images is annotated according to a Manifest corresponding to the scanned image, and small regions that pertain to the same category and are adjacent to or interconnected with each other are merged into a large region;
• and
• finally, features of all the small regions in each of the large regions constitute a feature cluster, and the classifier is trained according to the feature clusters of the known categories, for subsequent recognition.

A non-transitory computer readable storage medium, when instructions in the storage medium are executed by a processor of a device, the device is enabled to perform a method for automatic classification and recognition of cargoes, the method comprising:

• performing scanning and imaging for a container by using an X-ray scanning device to acquire a scanned image;
• segmenting the scanned image into small regions according to similarities in terms of gray scales and texture features, such that the gray scales and the texture features of the image in each small region are relatively uniform;
• extracting features of the small regions;
• generating a classifier according to annotated images, and/or storing or updating an existing classifier;
• and
• recognizing the small regions by using the classifier according to the extracted features, to obtain a probability of each small region pertaining to a certain category of cargoes, and merging small regions to obtain large regions each representing a category,
• wherein the method further comprises a training stage, and
• wherein in the training stage,
• firstly, after scanned images of cargoes in containers are acquired, each of the scanned images is pre-segmented into small regions according to similarities in terms of gray scales and texture features, and features of the small regions are extracted;
• subsequently, each of the scanned images is annotated according to a Manifest corresponding to the scanned image, and small regions that pertain to the same category and are adjacent to or interconnected with each other are merged into a large region;
• and
• finally, features of all the small regions in each of the large regions constitute a feature cluster, and the classifier is trained according to the feature clusters of the known categories, for subsequent recognition.