WO2007019140A2 - Boolean complement methods and systems for video image processing a region of interest - Google Patents
Boolean complement methods and systems for video image processing a region of interest Download PDFInfo
- Publication number
- WO2007019140A2 WO2007019140A2 PCT/US2006/029916 US2006029916W WO2007019140A2 WO 2007019140 A2 WO2007019140 A2 WO 2007019140A2 US 2006029916 W US2006029916 W US 2006029916W WO 2007019140 A2 WO2007019140 A2 WO 2007019140A2
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- WO
- WIPO (PCT)
- Prior art keywords
- region
- interest
- data
- video image
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- 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
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/22—Source localisation; Inverse modelling
Definitions
- Embodiments are generally related to video image processing methods and systems. Embodiments also relate to regions of interest (ROIs) associated with a video image. Embodiments additionally relate to techniques for specifying a region of interest (ROI) in a video image.
- ROIs regions of interest
- Embodiments additionally relate to techniques for specifying a region of interest (ROI) in a video image.
- Detecting a region of interest in images is a common feature of many image processing software applications.
- Conventional digital image recognition software routines for example, are capable of detecting an ROI.
- an image is composed of many objects that can be defined by pixels.
- a group of pixels is referred to as a region.
- a target is an object of interest.
- a prototype contains information about a type of target.
- An image-processing component may therefore detect a region in an image that matches the prototype.
- Algorithmic video image processing software applications typically require the specification of an ROI to define a limiting context in which to focus image- processing computations.
- the ROI may be, for example, a full video frame, or more typically, a subset of the full video image. Specifying an ROI that is smaller than the full image results in less computation and hence, less "real estate" data, to handle, which in turn can save processing time and enhance efficiency.
- Data indicative of a video image displayable with a display device associated with a data-processing apparatus can be scanned. At least one region of non-interest among the data can be identified, in response to compiling the data. Thereafter, at least one region of interest associated with the video image can be designed, such that the region of interest is equivalent to the data indicative of the video image minus the region of non-interest, thereby permitting the region of interest to be defined for focusing image-processing operations thereof upon the video image.
- the region of interest can comprise a geometrically regular shape or an irregular shape.
- the method, system and program product disclosed herein addresses the fact that certain video image processing applications may contain scenes that contain known physical region(s) within which there is a high probability of significant activities that are essentially noise in the context of the surveillance, security or access functions of the video image processing algorithms. In many cases, it is therefore more efficient to be able to describe the region of interest in terms of the full image minus (Boolean 'NOT') the regions of non-interest. Such a technique therefore obviates the construction of a complex ROI and can simplify the user interface requirements for specifying the ROI.
- FIG. 1 illustrates a block diagram of a representative data-processing apparatus in which a preferred embodiment can be implemented
- FIG. 2 illustrates a block diagram of a full video frame and a region of interest thereof
- FIG. 3 illustrates a block diagram of a full video frame and a region of non- interest in accordance with a preferred embodiment
- FIG. 4 illustrates a high-level flow chart of operations depicting logical operational steps that can be implemented in accordance with a preferred embodiment
- FIG. 5 illustrates an example of a complex Boolean complement region of interest of a sample video image, in accordance with an embodiment
- FIG. 6 illustrates the sample video image depicted in FIG. 5, in accordance with an embodiment
- FIG. 7 illustrates an excluded region of interest of the sample video image depicted in FIG. 5, in accordance with an embodiment
- FIG. 8 illustrates the outline of a particular area of the excluded region of interest indicated in FIG. 5, in accordance with an embodiment
- FIG. 9 depicts particular areas of the excluded region of interest indicated in FIG. 5, in accordance with an embodiment
- FIG. 10 illustrates an excluded region of interest minus the particular areas depicted in FIG. 9, in accordance with an embodiment
- FIG. 11 illustrates a complement region of interest and a region of interest in accordance with an embodiment
- FIG. 12 illustrates a region of interest in accordance with an embodiment
- FIG. 13 illustrates an identified region of interest in accordance with an embodiment.
- modules may constitute hardware modules, such as, for example, electronic components of a computer system. Such modules may also constitute software modules.
- a software module can be typically implemented as a collection of routines and data structures that performs particular tasks or implements a particular abstract data type.
- Software modules generally comprise instruction media storable within a memory location of a data-processing apparatus and are typically composed of two parts.
- a software module may list the constants, data types, variable, routines and the like that can be accessed by other modules or routines.
- a software module can be configured as an implementation, which can be private (i.e., accessible perhaps only to the module), and that contains the source code that actually implements the routines or subroutines upon which the module is based.
- the term module, as utilized herein can therefore refer to software modules or implementations thereof. Such modules can be utilized separately or together to form a program product that can be implemented through signal-bearing media, including transmission media and recordable media.
- the embodiments disclosed herein may be executed in a variety of systems, including a variety of computers running under a number of different operating systems.
- the computer may be, for example, a personal computer, a network computer, a mid-range computer or a mainframe computer.
- the computer is utilized as a control point of network processor services architecture within a local-area network (LAN) or a wide-area network (WAN).
- LAN local-area network
- WAN wide-area network
- FIG. 1 there is depicted a block diagram of a representative data-processing apparatus 110 (e.g., computer) in which a preferred embodiment can be implemented.
- processor CPU
- ROM Read-Only memory
- RAM Random-Access Memory
- PCI Peripheral Component Interconnect
- PCI Host Bridge 116 provides a low latency path through which processor 112 may directly access PCI , devices mapped anywhere within bus memory and/or input/output (I/O) address spaces.
- PCI Host Bridge 116 also provides a high bandwidth path for allowing PCI devices to directly access RAM 114.
- PCI local bus 120 Also attached to PCI local bus 120 are communications adapter 115, small computer system interface (SCSI) 118, and expansion bus-bridge 129.
- Communications adapter 115 is utilized for connecting data-processing apparatus 110 to a network 117.
- SCSI 118 is utilized to control high-speed SCSI disk drive 119.
- Expansion bus-bridge 129 such as a PCI-to-ISA bus bridge, may be utilized for coupling ISA bus 125 to PCI local bus 120.
- audio adapter 123 is attached to PCI local bus 120 for controlling audio output through speaker 124.
- PCI local bus 120 can further be connected to a monitory 102, which functions as a display (e.g., a video monitor) for displaying data and information for a user and for interactively displaying a graphical user interface (GUI).
- a monitory 102 which functions as a display (e.g., a video monitor) for displaying data and information for a user and for interactively displaying a graphical user interface (GUI).
- GUI graphical user interface
- additional peripheral components may be added or existing components can be connected to the system bus.
- the monitor 102 and the audio component 123 along with speaker 124 can instead be connected to system bus 131 , depending
- Data-processing apparatus 110 also preferably includes an interface such as a graphical user interface (GUI) and an operating system (OS) that reside within machine readable media to direct the operation of data-processing apparatus 110.
- GUI graphical user interface
- OS operating system
- Any suitable machine-readable media may retain the GUI and OS, such as RAM 114, ROM 113, SCSI disk drive 119, and other disk and/or tape drive (e.g., magnetic diskette, magnetic tape, CD-ROM, optical disk, or other suitable storage media).
- Any suitable GUI and OS may direct CPU 112.
- data-processing apparatus 110 preferably includes at least one network processor services architecture software utility (i.e., program product) that resides within machine-readable media, for example a custom defined service utility 108 within RAM 114.
- the software utility contains instructions (or code) that when executed on CPU 112 interacts with the OS.
- Utility 108 can be, for example, a program product as described herein.
- FIG. 2 illustrates a block diagram of an image-processing system 202 including a full video frame 202 and a region of interest (ROI) 204 thereof.
- ROI region of interest
- algorithmic video image processing software applications require the specification of an ROI 204 to define a limiting context in which to focus image- processing computations.
- the ROI 204 may be, for example, a full video frame; such as video frame 202 depicted in FIG. 2, or more typically, a subset of the full video image 202. Specifying an ROI that is smaller than the full image results in less computation.
- video image 202 can be displayed via a display unit, such as monitor 102 depicted in FIG. 1.
- the traditional definition of the ROI 204 is a closed polygon, circle or other close region within the full video image 202.
- One example application of such an ROI 204 involves the description of an ROI that includes images of background scene physical features (e.g., doorways, walkways, windows, high-value articles such as paintings, cash registers, etc.). In such cases a simple rectangular ROI 204 is
- FIG. 3 illustrates a block diagram of an image-processing system 300 including a full video frame 302 and a region of non-interest (RONI) 304 in accordance with a preferred embodiment.
- ROI region of non-interest
- FIG. 3 illustrates a block diagram of an image-processing system 300 including a full video frame 302 and a region of non-interest (RONI) 304 in accordance with a preferred embodiment.
- the region of interest is not limited to geometrically regular shapes, but can include any closed shape.
- a video frame such as video frame 302 depicted in FIG. 3 may have multiple regions of non-interest.
- Note video frame or image 302 can be displayed via a display device such as monitor 102 depicted in FIG. 1.
- Certain video image-processing applications may contain scenes that contain known physical region(s) within which there is a high-probability of significant activities that are essentially "noise" in the context of surveillance, security or access functions of the video image-processing methodology or system.
- Boolean generally refers to the system of logic/algebraic processes developed by George Boole, during the 19th century.
- the most well-known examples of Boolean are the AND, OR and NOT operators.
- Computers for example, use logic gates within their processors to carry out the Boolean instructions.
- FIG. 4 illustrates a high-level flow chart 400 of operations depicting logical operational steps that can be implemented in accordance with a preferred embodiment. Note that in FIGS. 1 and 3-4, identical or similar parts or elements are generally indicated by identical reference numerals.
- the methodology depicted in FIG. 4 can be implemented as a software module (s) and/or program product as described earlier.
- the logical operations depicted in FIG. 4 can be stored as a software module (e.g., utility 108 depicted in FIG. 1 ) and processed via a processor (e.g., see processor 112 of FIG. 1).
- the process is initiated and thereafter, as depicted at block 404, data indicative of a video image 302 can be compiled.
- the video image 302 can be displayed utilizing a display device associated with data-processing apparatus 100.
- one or more regions of non-interests (RONI's) can be identified among the data, in response to compiling the data.
- a single RONI 304 can thus be identified or a number of RONI's depending upon design considerations.
- one or more ROIs associated with the video image 302 can be designated.
- each ROI is equivalent to the data indicative of the video image 302 minus the RONI 1 thereby permitting the ROI to be defined for focusing image- processing operations thereof upon the video image 302.
- FIG. 5 illustrates an example of a complex Boolean complement region of interest of a sample video image 500, in accordance with an embodiment.
- a region of interest 502 is associated with region C, while excluded regions of interests 504 are associated with regions A and B.
- a legend 506 indicates a full field view of camera associated with letters i, j, k, and I. Note that FIG. 6 illustrates a full view of the sample video image depicted in FIG. 5, in accordance with an embodiment;
- FIG. 7 illustrates an excluded region of interest 700 of the sample video image depicted in FIG. 5, in accordance with an embodiment.
- the excluded ROI 700 is essentially equivalent to region B depicted in FIG. 5.
- regions or areas 702, 704 are specifically identified.
- FlG. 8 illustrates the outline of a particular area of the excluded region of interest indicated in FIG. 5, in accordance with an embodiment.
- FIG. 9 depicts particular areas 702, 704 of the excluded region of interest B indicated in FIG. 5 and as depicted in FIG. 7 in accordance with an embodiment.
- FIG. 10 illustrates an excluded region of interest 1000 minus the particular
- the ROI 1000 depicted in FIG. 10 is therefore analogous to the region B depicted in FIG. 5 but without areas 702, 704 as depicted in FIG. 9 and FIG. 7.
- FIG. 11 illustrates a complement region of interest 1102 and a region of interest 1104 in accordance with an embodiment.
- a sample video image 1102 is depicted in FIG. 7, with identified ROI's A, C, D, and E and a complement ROI F. Note that regions D and E are analogous to regions 702, 704 described earlier.
- FIG. 12 illustrates a region of interest 1200 in accordance with an embodiment.
- FIG. 13 illustrates an identified region of interest 1300 in accordance with an embodiment, which associated with region B.
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- Image Processing (AREA)
Abstract
Description
Claims
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| IL189199A IL189199A0 (en) | 2005-08-03 | 2008-02-03 | Boolean complement methods and systems for video image processing a region of interest |
| GB0801968A GB2442673A (en) | 2005-08-03 | 2008-02-04 | Boolean complement methods and systems for video image processing a region of interest |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US11/197,158 | 2005-08-03 | ||
| US11/197,158 US20070031038A1 (en) | 2005-08-03 | 2005-08-03 | Boolean complement methods and systems for video image processing a region of interest |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| WO2007019140A2 true WO2007019140A2 (en) | 2007-02-15 |
| WO2007019140A3 WO2007019140A3 (en) | 2007-07-26 |
Family
ID=37717636
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/US2006/029916 Ceased WO2007019140A2 (en) | 2005-08-03 | 2006-08-01 | Boolean complement methods and systems for video image processing a region of interest |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20070031038A1 (en) |
| CN (1) | CN101273383A (en) |
| GB (1) | GB2442673A (en) |
| IL (1) | IL189199A0 (en) |
| WO (1) | WO2007019140A2 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013003860A1 (en) * | 2011-06-30 | 2013-01-03 | Yale University | Subject sensing in an environment |
| CN109286824B (en) * | 2018-09-28 | 2021-01-01 | 武汉斗鱼网络科技有限公司 | Live broadcast user side control method, device, equipment and medium |
| CN110363144A (en) * | 2019-07-16 | 2019-10-22 | 中国民航科学技术研究院 | An aircraft door switch state detection system and method based on image processing technology |
| US11157741B2 (en) * | 2019-08-13 | 2021-10-26 | International Business Machines Corporation | Determining the state of infrastructure in a region of interest |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB9118782D0 (en) * | 1991-09-03 | 1991-10-16 | British Broadcasting Corp | Video image processing |
| GB2322269B (en) * | 1997-02-13 | 2001-08-22 | Quantel Ltd | A video image processing apparatus and method |
| JPH10275460A (en) * | 1997-04-01 | 1998-10-13 | Sega Enterp Ltd | Memory device and image processing device using the same |
| US6310982B1 (en) * | 1998-11-12 | 2001-10-30 | Oec Medical Systems, Inc. | Method and apparatus for reducing motion artifacts and noise in video image processing |
| US6404460B1 (en) * | 1999-02-19 | 2002-06-11 | Omnivision Technologies, Inc. | Edge enhancement with background noise reduction in video image processing |
| US6678413B1 (en) * | 2000-11-24 | 2004-01-13 | Yiqing Liang | System and method for object identification and behavior characterization using video analysis |
| US7231086B2 (en) * | 2002-05-09 | 2007-06-12 | General Dynamics C4 Systems, Inc. | Knowledge-based hierarchical method for detecting regions of interest |
| US6757434B2 (en) * | 2002-11-12 | 2004-06-29 | Nokia Corporation | Region-of-interest tracking method and device for wavelet-based video coding |
| JP4373682B2 (en) * | 2003-01-31 | 2009-11-25 | 独立行政法人理化学研究所 | Interesting tissue region extraction method, interested tissue region extraction program, and image processing apparatus |
-
2005
- 2005-08-03 US US11/197,158 patent/US20070031038A1/en not_active Abandoned
-
2006
- 2006-08-01 WO PCT/US2006/029916 patent/WO2007019140A2/en not_active Ceased
- 2006-08-01 CN CNA2006800353295A patent/CN101273383A/en active Pending
-
2008
- 2008-02-03 IL IL189199A patent/IL189199A0/en unknown
- 2008-02-04 GB GB0801968A patent/GB2442673A/en not_active Withdrawn
Also Published As
| Publication number | Publication date |
|---|---|
| IL189199A0 (en) | 2008-06-05 |
| GB2442673A (en) | 2008-04-09 |
| GB0801968D0 (en) | 2008-03-12 |
| WO2007019140A3 (en) | 2007-07-26 |
| US20070031038A1 (en) | 2007-02-08 |
| CN101273383A (en) | 2008-09-24 |
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