Detection of prohibited objects concealed in an item, using image processing

A method comprising, by one or more processing circuitries:

• obtaining an image of an item acquired by an acquisition device,
• performing a first detection using at least one first deep neural network, to detect at least one given area of the image comprising at least part of a given unprohibited concealing element of the item which enables concealment of a prohibited object, wherein the first detection is not directed to identifying prohibited objects or materials corresponding to prohibited objects,
• determining that the given unprohibited concealing element belongs to a named category of unprohibited concealing elements associated with certain physical characteristic comprising at least one of material or shape wherein a primary purpose of the given unprohibited concealing element comprises at least one of mechanical reinforcement, fastening or identification,
• using the named category of the given unprohibited concealing element to select a given second neural network among a plurality of different second neural networks operative to detect prohibited objects concealed using concealing elements,
• wherein the given second neural network has been trained to detect in an image presence of a prohibited object concealed using a concealing element of said named category,
• performing a second detection comprising using the given second neural network to detect whether the given area comprises a prohibited object, and
• performing an action in response to detection of a presence of a prohibited object in the image.

A non-transitory storage device readable by one or more processors, tangibly embodying a program of instructions executable by the one or more processors to perform:

• obtaining an image of an item acquired by an acquisition device,
• performing a first detection using at least one first deep neural network, to detect at least one given area of the image comprising at least part of a given unprohibited concealing element of the item which enables concealment of a prohibited object, wherein the first detection is not directed to identifying prohibited objects or materials corresponding to prohibited objects,
• determining that the given unprohibited concealing element belongs to a named category of unprohibited concealing elements associated with certain physical characteristic comprising at least one of material or shape, wherein a primary purpose of the given unprohibited concealing element comprises at least one of mechanical support, reinforcement, fastening, or identification;
• using the named category of the given unprohibited concealing element to select a given second neural network among a plurality of different second neural networks operative to detect prohibited objects concealed using concealing elements,
• wherein the given second neural network has been trained to detect in an image presence of a prohibited object concealed using a concealing element of said named category,
• performing a second detection comprising using the given second neural network to detect whether the given area comprises a prohibited object, and
• performing an action in response to detection of a presence of a prohibited object in the image.