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: 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: The present disclosure provides a semiconductor detector. The semiconductor detector comprises: a detector crystal including a crystal body, an anode and a cathode; a field enhance electrode for applying a voltage to the detector crystal; an insulating material disposed between the field enhanced electrode and a surface of the detector crystal. The semiconductor detector further comprises a field enhanced electrode circuit board having a bottom connection layer in contact with the surface of the detector crystal and a top layer opposite to the bottom connection layer, wherein the top layer is connected to a high voltage input terminal of the semiconductor detector, and an insulating material is provided between the bottom connection layer and the detector surface of the detector crystal.

Abstract: An inspection apparatus and a method for segmenting an Image of a vehicle are disclosed. An X-ray transmission scanning is performed on the vehicle to obtain a transmission image. Each pixel of the transmission image is labeled with a category tag, by using a trained convolutional network. Images of respective parts of the vehicle are determined according to the category tag for each pixel. With the above solutions, it is possible to segment the images of respective parts of a vehicle more accurately in the situations that are complicated or have large variety kinds of vehicles.

Abstract: The present disclosure discloses a method and system for inspecting cargoes. The method comprises: acquiring a transmission image of the inspected cargoes; processing the transmission image to acquire an interested region; extracting features from the interested region, and determining cargo information of the inspected cargoes according to the extracted features; and providing a proposed treatment suggestion of the cargoes based on the determined cargo information and at least a part of information in a manifest. The above solution can facilitate an image judgment person to accurately judge whether the concerned cargoes are allowed to pass.

Abstract: An inspection device and a method for detecting a firearm are disclosed. X-ray inspection is performed on an inspected object to obtain a transmission image. A plurality of candidate regions in the transmission image are determined using a trained firearm detection neural network. The plurality of candidate regions are classified using the firearm detection neural network to determine whether there is a firearm included in the transmission image. With the above solution, it is possible to determine more accurately whether there is a firearm included in a container/vehicle.

Abstract: An inspection device and a method for detecting a firearm in a luggage are disclosed. The method comprises: performing X-ray inspection on the luggage to obtain a transmission image; determining a plurality of candidate regions in the transmission image using a trained firearm detection neural network; and classifying the plurality of candidate regions using the detection neural network to determine whether there is a firearm included in the transmission image. With the above solutions, it is possible to determine more accurately whether there is a firearm included in a luggage. In other embodiments, after a firearm is detected using the above method, a label is marked in the image to prompt an image judger.

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: A method, a device and a security system for image data processing based on VR or AR are disclosed. In one aspect, an example image data processing method includes reconstructing, based on three-dimensional (3D) scanned data of a containing apparatus in which objects are contained, a 3D image of the containing apparatus and the objects contained in the containing apparatus. The reconstructed 3D image is stereoscopically displayed. Manipulation information is determined for at least one of the objects in the containing apparatus based on positioning information and action information of a user. At least a 3D image of the at least one object is reconstructed based on the determined manipulation information. The at least one reconstructed object is presented on the displayed 3D image.

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: 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: The present disclosure discloses an inspection device and a method for inspecting a container. Transmission scanning is performed on the inspected container using a scanning device including a sparse area array detector to obtain scan data. Digital focusing is performed at a specific depth position in a depth direction. Defocused pixel values are filtered out to obtain a slice image at the specific depth position. It is judged whether dangerous articles or suspicious articles are included in the slice image.

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: A vehicle inspection method is disclosed, comprising steps of: implementing a ray scanning inspection on an inspected vehicle, so as to obtain a ray scanning inspection image of the inspected vehicle; extracting vehicle characteristic information; comparing the vehicle characteristic information of the inspected vehicle to vehicle reference characteristics stored in a database, selecting a closest vehicle reference characteristic which is closest to the vehicle characteristic information, and finding out a closest ray transmission reference image on the basis of a corresponding relationship between the vehicle reference characteristics and ray transmission reference images stored in the storage unit; determining a first distinguishing area of the ray scanning inspection image from the closest ray transmission reference image by comparing the ray scanning inspection image of the inspected vehicle to the closest ray transmission reference image. A vehicle inspection system is also disclosed.

Abstract: The present disclosure provides a method for recognizing an article using a multi-energy spectrum X-ray imaging system and a multi-energy spectrum X-ray imaging system. The method comprises: recognizing an application scenario and/or priori information of the article; selecting a parameter mode suitable for the article from a plurality of parameter modes stored in the multi-energy spectrum X-ray imaging system based on the recognized application scenario and/or priori information; and recognizing the article using the selected parameter mode, wherein the plurality of parameter modes are obtained by optimizing system parameters of the multi-energy spectrum X-ray imaging system under a specific condition using a training sample library for various articles.

Abstract: Inspection devices and inspection methods are disclosed. The inspection method includes: performing X-ray scanning on an object being inspected so as to generate an image of the object being inspected; dividing the image of the object being inspected to determine at least one region of interest; detecting interaction between a cosmic ray and the region of interest to obtain a detection value; calculating a scattering characteristic value and/or an absorption characteristic value of the cosmic ray in the region of interest based on size information of the region of interest and the detection value; and discriminating a material attribute of the region of interest by means of the scattering characteristic value and/or the absorption characteristic value. With the above technical solutions, inspection accuracy and inspection efficiency may be improved.

Abstract: The present disclosure provides method and apparatus for marking a target in a 3D image. The method include steps of: acquiring Computed Tomography (CT) image data of a scene; rendering a 3D image of the scene using ray casting based on the CT image data; removing a transparent region from the 3D image based on a fixed 2D transfer function; and marking the target in the 3D image.

Abstract: The disclosure provides a detector, and a detecting system and method for dividing energy regions intelligently.

Abstract: The present disclosure provides a semiconductor detector. The semiconductor detector comprises: a detector crystal including a crystal body, an anode and a cathode; a field enhance electrode for applying a voltage to the detector crystal; an insulating material disposed between the field enhanced electrode and a surface of the detector crystal. The semiconductor detector further comprises a field enhanced electrode circuit board having a bottom connection layer in contact with the surface of the detector crystal and a top layer opposite to the bottom connection layer, wherein the top layer is connected to a high voltage input terminal of the semiconductor detector, and an insulating material is provided between the bottom connection layer and the detector surface of the detector crystal.

Abstract: The present disclosure provides an apparatus for processing signals for a plurality of energy regions, and a system and method for detecting radiation of a plurality of energy regions. The apparatus for processing signals for a plurality of energy regions may comprise: a first processor, configured to receive a signal from a detector and process the received signal to generate a gated signal, wherein a turn-on period of the gated signal represents magnitude of the received signal; and a second processor, configured to receive the gated signal from the first processor, and determine one of the plurality of energy regions to which the received signal belongs according to the turn-on period of the gated signal, so as to count signals within the determined energy region.