Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
  • G01V5/00—Prospecting or detecting by the use of ionising radiation, e.g. of natural or induced radioactivity
  • G01V5/20—Detecting prohibited goods, e.g. weapons, explosives, hazardous substances, contraband or smuggled objects
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/80—Geometric correction
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/0002—Inspection of images, e.g. flaw detection
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
  • G06V10/00—Arrangements for image or video recognition or understanding
  • G06V10/20—Image preprocessing
  • G06V10/32—Normalisation of the pattern dimensions
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
  • G06V10/00—Arrangements for image or video recognition or understanding
  • G06V10/88—Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters
  • G06V10/89—Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters using frequency domain filters, e.g. Fourier masks implemented on spatial light modulators
  • G06V10/893—Image or video recognition using optical means, e.g. reference filters, holographic masks, frequency domain filters or spatial domain filters using frequency domain filters, e.g. Fourier masks implemented on spatial light modulators characterised by the kind of filter
• • G—PHYSICS
  • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
  • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
  • G09B19/00—Teaching not covered by other main groups of this subclass
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
  • G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
  • G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10116—X-ray image
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/30—Subject of image; Context of image processing
  • G06T2207/30108—Industrial image inspection
  • G06T2207/30112—Baggage; Luggage; Suitcase
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
  • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
  • G06V2201/05—Recognition of patterns representing particular kinds of hidden objects, e.g. weapons, explosives, drugs

Definitions

• the present invention relates generally to security systems and, more particularly, to methods and systems for screening receptacles including, for example, luggage, mail parcels or cargo containers, to identify certain objects located therein, where such methods and systems implement image distortion correction functionality.
• security screening systems make use of devices generating penetrating radiation, such as x-ray devices, to scan individual pieces of luggage to generate an image conveying the contents of the luggage.
• the image is displayed on a screen and is examined by a human operator whose task it is to detect and possibly identify, on the basis of the image, potentially threatening objects located in the luggage.
• some form of object recognition technology may be used to assist the human operator.
• a deficiency with current systems is that they are mostly reliant on the human operator to detect and identify potentially threatening objects.
• the performance of the human operator greatly varies according to such factors as poor training and fatigue.
• the detection and identification of threatening objects is highly susceptible to human error.
• failure to identify a threatening object, such as a weapon for example may have serious consequences, such as property damage, injuries and fatalities.
• Another deficiency with current systems is that the labour costs associated with such systems are significant since human operators must view the images.
• the present application seeks to provide an apparatus suitable for screening a receptacle.
• the apparatus comprises an input for receiving an image signal associated with the receptacle, the image signal conveying an input image related to contents of the receptacle, the image signal having been produced by a device that is characterized by introducing distortion into the input image.
• the apparatus also comprises a processing unit in communication with the input, and operative for: applying a distortion correction process to the image signal to remove at least part of the distortion from the input image, thereby to generate a corrected image signal conveying at least one corrected image related to the contents of the receptacle; processing the corrected image signal in combination with a plurality of data elements associated with a plurality of target objects in an attempt to detect a presence of at least one of said target objects in the receptacle; and generating a detection signal in response to detection of the presence of at least one of said target objects in the receptacle.
• the apparatus further comprises an output for releasing the detection signal.
• the present application seeks to provide an apparatus for detecting the presence of one or more prohibited objects in a receptacle.
• the apparatus comprises an input for receiving an input image conveying graphic information regarding contents of a receptacle, the image having been produced by a device that introduces distortion into the input image; a distortion correction functional unit operable for processing the input image to remove at least part of the distortion from the input image in order to derive at least one corrected image; an optical correlator operable for processing the at least one corrected image in an attempt to detect whether at least one of said one or more prohibited objects is depicted in at least one of the at least one corrected image; and an output for releasing a signal in response to detecting that at least one of said one or more prohibited objects is depicted in at least one of the at least one corrected image.
• the present application seeks to provide a method for screening a receptacle, which comprises receiving an image signal associated with the receptacle, the image signal conveying an input image related to contents of the receptacle, the image signal having been produced by a device that is characterized by introducing distortion into the input image; applying a distortion correction process to the image signal to remove at least part of the distortion from the input image, thereby to generate a corrected image signal conveying at least one corrected image related to the contents of the receptacle; processing the corrected image signal in combination with a plurality of data elements associated with a plurality of target objects in an attempt to detect a presence of at least one of said target objects in the receptacle; generating a detection signal in response to detection of the presence of at least one of said target objects in the receptacle; and releasing the detection signal.
• the present application seeks to provide a computer-readable medium comprising computer-readable program code which, when interpreted by a computing apparatus, causes the computing apparatus to execute a method of screening a receptacle.
• the computer-readable program code comprises first computer-readable program code for causing the computing apparatus to be attentive to receipt of an image signal associated with the receptacle, the image signal conveying an input image related to contents of the receptacle, the image signal having been produced by a device that is characterized by introducing distortion into the input image; second computer-readable program code for causing the computing apparatus to apply a distortion correction process to the image signal to remove at least part of the distortion from the input image, thereby to generate a corrected image signal conveying at least one corrected image related to the contents of the receptacle; third computer-readable program code for causing the computing apparatus to process the corrected image signal in combination with a plurality of data elements associated with a plurality of target objects in an attempt to detect a presence of at least one of said target
• the database 110 has been shown in Figure 1 to be a component separate from the apparatus 106, it will be appreciated that in certain embodiments the database 110 may be part of apparatus 106 and that such implementations do not detract from the spirit of the invention. In addition, it will also be appreciated that in certain implementations, the database 110 is shared between multiple apparatuses 106.
• the first input 310 is for receiving an image signal 150 associated with the receptacle 104 from the image generation device 102 (shown in Figure 1). It is recalled that the image signal 150 conveys the input image 800 related to the contents of the receptacle 104.
• the second input 314 is for receiving data elements from the database 110, such data elements being associated with target objects. It will be appreciated that in embodiments where the database 110 is part of apparatus 106, the second input 314 may be omitted.
• the output 312 is for releasing the detection signal 160 conveying the presence of one or more target objects in the receptacle 104. The detection signal 160 is transmitted towards the output module 108.
• B- SEGMENTATION Thresholding; Binary or multilevel; Hysteresis based; Statistics/histogram analysis; Clustering; Region growing; Splitting and merging; Texture analysis; Watershed; Blob labeling; C- GENERAL DETECTION: Template matching; Matched filtering; Image registration; Image correlation; Hough transform;
• F- FREQUENCY ANALYSIS Fourier Transform; Wavelets;
• Bayesian classifier Principal component analysis; Binary tree; Graphs; Neural networks; Genetic algorithms; Markov random fields.
• Step 510 the detection signal generation module 306 generates the aforesaid detection signal 160 conveying the presence of the particular target object in the receptacle 104.
• the detection signal 160 is released via the output 312.
• the detection signal 160 may simply convey the fact that the particular target object has been detected as present in the receptacle 104, without necessarily specifying the identity of the particular target object.
• the detection signal 160 may convey the actual identity of the particular target object.
• the detection signal 160 may include information related to the positioning of the particular target object within the receptacle 104 and optionally a target object identifier data element associated with the particular target object.
• the correlation operation may be implemented using a digital correlator.
• the correlation operation is computationally intensive and, in certain implementations requiring real-time performance, the use of a digital correlator may not provide suitable performance. Under such conditions, an optical correlator may be preferred.
• an optical correlator performs the correlation operation physically through light-based computation, rather than by using software running on a silicon- based computer, which allows computations to be performed at a higher speed than is possible with a software implementation and thus provides for improved real-time performance.
• Specific examples of implementation of the optical correlator include a joint transform correlator (JTC) and a focal plane correlator (FPC).
• JTC joint transform correlator
• FPC focal plane correlator
• Figures 8A and 8C Two specific non- limiting embodiments of a suitable optical correlator are shown in Figures 8A and 8C.
• the optical correlator effects a Fourier transformation 840 of a given corrected image related to the contents of the receptacle 104.
• the optical correlator effects a complex conjugate Fourier transformation 840' of a particular image 804 of a particular target object obtained from the database 1 10.
• Image processing and enhancement, as well as distortion pre-emphasis, can also be performed on the particular image 804 to obtain better matching performance depending on the environment and application.
• the result of the two Fourier transformations is multiplied 820.
• the optical correlator then processes the result of the multiplication of the two Fourier transforms by applying another optical Fourier transform (or inverse Fourier transform) 822.
• the resulting signal is captured by a camera (or charge coupled device) 912 at what is referred to as the correlation plane, which yields the correlation output, shown at Figure 8B.
• the data elements in the database 1 10 include data indicative of the Fourier transform of the images of the target objects that the system 100 is designed to detect.
• Such data elements will be referred to herein after as “templates” (or “filters”) for particular target objects.
• the templates (or filters) are digitally pre-computed such as to improve the speed of the correlation operation when the system 100 is in use.
• Image processing and enhancement, as well as distortion pre-emphasis can also be performed on the image of a particular target object to obtain better matching performance depending on the environment and application.
• the data element accessed at step 503 conveys a particular template (or filter) 804' for a particular image 804.
• the image comparison module 302 implements an optical correlator for effecting a Fourier transformation 840 of a given corrected image related to the contents of the receptacle 104.
• the result is multiplied 820 with the (previously computed) template (or filter) 804' for the particular image 804, as accessed from the database 110.
• the optical correlator then processes the product by applying the optical Fourier transform (or inverse Fourier transform) 822.
• the resulting signal is captured by the camera 912 at the correlation plane, which yields the correlation output, shown at Figure 8B.
• the correlation output is released for transmission to the detection signal generator 306 where it is analyzed.
• a peak in the correlation output indicates a match between the input image 800 related to the contents of the receptacle 104 and the template (or filter) 804' for the particular image 804.
• the result of the processing is then conveyed to the user by output module 108.
• a MACE (Minimum Average Correlation Energy) filter is used to generate a template (or filter) for a given target object.
• the MACE filter combines several different 2D projections of a given object and encodes them in a single MACE filter instead of having one 2D projection per filter.
• One of the benefits of using MACE filters is that the resulting database 110 would take less space since it would include fewer items. Also, since the number of correlation operations needed to identify a single target object would be reduced, the total processing time to determine whether a given object is present would also be reduced.
• Another way of reducing the processing time of the correlation operation is to take advantage of the linear properties of the Fourier transform.
• a composite image can be formed, herein referred to as a mosaic.
• the correlation is computed simultaneously on all the sub-images without incurring any substantial time penalty.
• a mosaic may contain several different target objects or several different orientations of the same target object or a combination of both.
• Figure 7 depicts a mosaic including a target object in various orientations and scales. The parallel processing capabilities of a mosaic effectively increase the throughput of an optical correlator.
• FIG. 9 The inner workings of the aforementioned non-limiting example optical correlator are illustrated in Figure 9.
• a laser source 900 that generates a coUimated coherent light beam used to project images across the correlator.
• the light beam is directed first through a small set of lenses 902 used to expand its diameter in order to illuminate, in parallel, the whole surface of a first liquid crystal display (LCD) screen 904.
• the input image 800 related to the contents of the receptacle 104 is displayed on the first LCD screen 904 either .through a direct camera interface or provided as a VGA image by a computing device.
• the first LCD screen 904 is illuminated by the light beam and the image is propagated through the correlator.
• the input image 800 related to the contents of the receptacle 104, which is captured by the camera is that of a gun on a conveyor belt.
• the light beam modulated by the first image on the first LCD screen 904 is then propagated through a second set of lenses 906, referred to as a Fourier lens since it performs the equivalent of the Fourier transform mathematical operation.
• the inherent properties of light are used to physically perform the appropriate calculations. Specifically, the propagation of light is a function which corresponds to the kernel of the Fourier transform operation, thus the propagation of light along the axis of a Fourier Jens represents a sufficiently strong approximation of this natural phenomenon to assert that the light beam undergoes a Fourier transform. Otherwise stated, a lens has the inherent property of performing a Fourier transform on images observed at its front focal plane, provided that this image is displayed at its back focal plane.
• the Fourier transform is a mathematical tool used to convert the information present within an object's image into its frequency representation.
• an image can be seen as a superposition of various spatial frequencies and the Fourier transform is a mathematical operation used to compute the intensity of each of these frequencies within the image.
• the spatial frequencies represent the rate of variation of image intensity in space. Consequently, a smooth or uniform pattern mainly contains low frequencies. Sharply contoured patterns, by contrast, exhibit a higher frequency content.
• a correlation operation can be mathematically described by:
• Figure 10 depicts the Fourier transform of the spatial domain image of a number '2'. It can be seen that most of the energy (bright areas) is contained in the central portion of the Fourier transform image which correspond to low spatial frequencies (the images are centred on the origin of the Fourier plane). The energy is somewhat more dispersed in the medium frequencies and is concentrated in orientations representative of the shape of the input image. Finally, little energy is contained in the upper frequencies.
• the right-hand-side image shows the phase content of the Fourier transform. The phase is coded from black (0°) to white (360°).
• Matched filters are specifically adapted to respond to one image in particular: they are optimized to respond to an object with respect to its energy content.
• the contour of an object corresponds to its high frequency content. This can be easily understood as the contour represent areas where the intensity varies rapidly (hence a high frequency).
• the matched filter can be divided by its module (the image is normalized), over the whole Fourier transform image. The resulting filter is called a Phase-Only Filter (POF) and is defined by:
• phase only filters PPF
• the computed filter is then called a composite filter since it incorporates the properties of many images (note that it is irrelevant whether the images are averaged before or after the Fourier transform operator is applied, provided that in the latter case, the additions are performed taking the
• composite filters are composed of the response of individual POF filters to the same symbol. Mathematically, this can be expressed by:
• h con ⁇ (X' y) aa h a ( ⁇ > y) + a bhb ( ⁇ > y) + - - - + a ⁇ h ⁇ ( ⁇ ' y) (5)
• a system for screening people includes components similar to those described in connection with the system depicted in Figure 1.
• the image generation device 102 is configured to scan a person and possibly to scan the person along various axes to generate multiple images associated with the person.
• the image(s) associated with the person convey information related to the objects carried by the person.
• Figure 11 depicts two images associated with a person suitable for use in connection with a specific implementation of the system. Each image is then processed in accordance with the method described in the present specification to detect the presence of target objects on the person.
• FIG 12 including a processing unit 1302 and a memory 1304 connected by a communication bus.
• the memory includes data 1308 and program instructions 1306.
• the processing unit 1302 is adapted to process the data 1308 and the program instructions 1306 in order to implement the functional blocks described in the specification and depicted in the drawings.
• the digital computer 1300 may also comprise an I/O interface 1310 for receiving or sending data elements to external devices.
• the above-described apparatus 106 can be implemented on a dedicated hardware platform where electrical/optical components implement the functional blocks described in the specification and depicted in the drawings. Specific implementations may be realized using ICs, ASICs, DSPs, FPGAs, an optical correlator, digital correlator or other suitable hardware platform.
• the optical correlator suitable for use in the system described herein includes a video input and a digital input.
• the video input is suitable for receiving a signal derived from an image generation device and the digital input is suitable for receiving a signal derived from images in a database.
• the video input is suitable for receiving a signal in an NTSC compatible format and the digital input suitable for receiving a signal in a VGA compatible format.
• the digital input suitable for receiving a signal in a VGA compatible format may be replaced by any other suitable digital input interface adapted for receiving signals of lower or higher resolution that the VGA compatible format signal.
• the video input suitable for receiving a signal in an NTSC compatible format may be replaced by any other suitable analog or digital video signal interface suitable for receiving signals in suitable formats such as, but not limited to, PAL and SECAM.
• the optical correlator is adapted to process an image received at the video input having an area of 640x480 pixels.
• the video input is replaced by a second digital input adapted for receiving an image signal in any suitable digital image format.
• the image generation device 102 (shown in figure 1) generates a digital format image and communicates the latter to the apparatus 106.
• the digital image generated by the image generation device 102 can be processed directly without the requirement of effecting an analog-to-digital conversion at the apparatus 106.
• a single optical correlator can be shared by multiple image generation devices.
• conventional parallel processing techniques can be used for sharing a common hardware resource.

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• 2007
  • 2007-05-04 EP EP07719704A patent/EP2016532A4/de not_active Withdrawn
  • 2007-05-04 WO PCT/CA2007/000779 patent/WO2007131328A1/en not_active Ceased
  • 2007-05-11 CA CA2651131A patent/CA2651131C/en active Active
  • 2007-05-11 WO PCT/CA2007/000840 patent/WO2007131348A1/en not_active Ceased
  • 2007-05-11 EP EP07719764A patent/EP2016572A4/de not_active Withdrawn
  • 2007-05-11 CA CA2708600A patent/CA2708600A1/en not_active Abandoned

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