Abstract:
An inspection method and system for inspecting whether there is any liquor in goods is provided. The method includes: acquiring a radiation image of goods being inspected; processing on the radiation image to obtain an ROI; inspecting on the ROI using a liquor goods inspection model to determine if the ROI of the radiation image contains liquor goods. The above solution performs liquor inspection on scanned images of goods, especially containers, so as to intelligently assist the image inspectors.
Abstract:
The present disclosure provides a method and a system for inspecting goods. The method comprises steps of: obtaining a transmission image of inspected goods; processing the transmission image to obtain a suspicious region; extracting local texture features of the suspicious region and classifying the local texture features of the suspicious region based on a pre-created model to obtain a classification result; extracting a contour line shape feature of the suspicious region and comparing the contour line shape feature with a pre-created standard template to obtain a comparison result; and determining that the suspicious region contains a high atomic number matter based on the classification result and the comparison result.
Abstract:
The present disclosure discloses an inspection method and device. The method comprises steps of acquiring a perspective image of an inspected object; processing the perspective image to obtain a region of interest; and automatically detecting the region of interest using a cigarette model, to determine whether the region of interest of the perspective image belongs to a cigarette. In the present disclosure, cigarette detection is implemented on a scanned image of goods, particularly a container, which can avoid the problem of detection vulnerability and poor effect of manual image judgment for the conventional manner, and is of significance in fighting against cigarette smuggling.
Abstract:
Methods for extracting a shape feature of an object and security inspection methods and apparatuses. Use is made of CT's capability of obtaining a 3D structure. The shape of an object in an inspected luggage is used as a feature of a suspicious object in combination with a material property of the object. For example, a false alarm rate in detection of suspicious explosives may be reduced.
Abstract:
Disclosed are object detection method, display methods and apparatuses. The method includes obtaining slice data of inspected luggage in the CT system; generating 3D volume data of objects in the luggage from the slice data; for each object, determining a semantic description including at least a quantifier description of the object based on the 3D volume data; and upon reception of a user selection of an object, presenting the semantic description of the selected object while displaying a 3D image of the object. The above solutions can create a 3D model for objects in the inspected luggage in a relatively accurate manner, and thus provide better basis for subsequent shape feature extraction and security inspection, and reduce omission factor.
Abstract:
A method for inspecting a container and an inspection device are disclosed. X-ray scanning is performed on the inspected container to obtain a scanned image. The scanned image is processed to obtain a region of interest. Features of texture units included in the region of interest are calculated. Local descriptions of the texture units are formed based on the features of the texture units. Distinction of each local point is calculated from a local description of each of the texture units so as to obtain a local distinct map of the region of interest. It is determined whether there is an article which is secretly carried in the inspected container using the local distinct map.
Abstract:
The present disclosure discloses a method and system for identifying a part of a vehicle and a vehicle inspection system. The method includes: acquiring a vehicle body image sequence of a vehicle to be identified; reconstructing the vehicle body by using a first vehicle body reconstruction model generated through a deep learning algorithm and on the basis of the vehicle body image sequence, so as to acquire a vehicle body reconstruction image of the vehicle to be identified; and identifying a boundary identifier of the vehicle to be identified on the basis of the vehicle body reconstruction image of the vehicle to be identified.
Abstract:
The present disclosure relates to a fluoroscopic inspection system for automatic classification and recognition of cargoes. The system includes: an image data acquiring unit, configured to perform scanning and imaging for a container by using an X-ray scanning device to acquire a scanned image; an image segmenting unit, configured to segment the scanned image into small regions each having similar gray scales and texture features; a feature extracting unit, configured to extract features of the small regions; a training unit, configured to generate a classifier according to annotated images; and a classification and recognition unit, configured to 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.
Abstract:
Disclosed are a retrieving system and a retrieving method based on content of fluoroscopic images, the retrieving system comprising: a pre-classifying module, configured to pre-classify fluoroscopic images; an image content feature extracting module, configured to perform feature extraction for contents of the fluoroscopic images; an image representing module, configured to construct an image representation vector; a retrieving module, configured to construct a result of preliminary candidates; a diversified filtering module, configured to filter the result of preliminary candidates, select an image subset capable of covering a plurality of article categories, and thereby construct a diversified retrieval result; a correlation feedback regulating module, configured to receive information feedback on the retrieval result from a user, and update the retrieval model; and an interacting module, configured to display the retrieval result, and collect feedback on user's satisfaction of the retrieval result.
Abstract:
An inspection method and system for inspecting whether there is any liquor in goods is provided. The method includes: acquiring a radiation image of goods being inspected; processing on the radiation image to obtain an ROI; inspecting on the ROI using a liquor goods inspection model to determine if the ROI of the radiation image contains liquor goods. The above solution performs liquor inspection on scanned images of goods, especially containers, so as to intelligently assist the image inspectors.