Patent Abstract:
A system and method for dating gelatin silver photographic paper is provided. The system and method includes providing a database management system having physical texture characteristic profiles. The system implements a program of instructions to determine a probable date range or source for each textural characteristic profile. The system includes LED sources disposed around an inner surface of a dome; an LED controller, and a CCD imager microscope.

Full Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     The present application is related to, claims the earliest available effective filing date(s) from (e.g., claims earliest available priority dates for other than provisional patent applications; claims benefits under 35 USC §119(e) for provisional patent applications), and incorporates by reference in its entirety all subject matter of the following listed application(s) (the “Related Applications”) to the extent such subject matter is not inconsistent herewith; the present application also claims the earliest available effective filing date(s) from, and also incorporates by reference in its entirety all subject matter of any and all parent, grandparent, great-grandparent, etc. applications of the Related Application(s) to the extent such subject matter is not inconsistent herewith: 
     U.S. provisional patent application 61/860,844 entitled “A System and Method for Dating Textured Gelatin Silver Paper”, naming Paul Messier and Andrew Messier as inventors, filed 31 Jul. 2013. 
    
    
     BACKGROUND 
     1. Field of Use 
     These teachings relate generally to forensic photograph dating and more particularly to systems employing digital computers for determining the probabilistic date of a physical characteristic associated with a photograph. The teachings may also relate to any field where reflectance transformation imaging is employed, such as, for example, the fields of ballistics investigation or numismatics. 
     2. Description of Prior Art (Background) 
     A photographic print&#39;s date is elementary to the understanding of the work, its historical context and the photographer&#39;s artistic intent. It carries implications for its treatment, display and storage and can manifestly influence its market value. Recently, photographs have become the target of forgers, and as the market value of these works increase, so will forgery continue. The detection of forged photography is particularly difficult in the context of today&#39;s imaging technology as experts must be able to tell the difference between originals and reprints. For example, a forger in possession of photo-negatives would allow the forger to print an unlimited number of prints, which then can be passed off as original. 
     Texture is a defining attribute of photographic paper. Starting in the early 20th century, manufacturers manipulated texture to differentiate their products and to satisfy the aesthetic and functional requirements of photographers. Prior to WWII, when black and white silver gelatin paper was the dominant photographic medium, dozens of manufacturers worldwide produced a wide array of surfaces. From this period a book of specimen prints by the Belgian company Gevaert lists twenty five different surfaces comprising combinations of texture, reflectance, color and paper thickness (Gevaert Company of America c. 1935). Around the same time, a sample book from the Defender Company of Rochester N.Y. lists twenty seven surfaces (Defender Photo Supply Company c. 1935), Mimosa twenty six (Mimosa AG c. 1935) and Kodak twenty two (Eastman Kodak c. 1935). Each listed surface was proprietary to the different manufacturers and each was used across their multiple brands of paper with changes, additions, and deletions occurring over a span of many years. 
     Texture, a vital factor in the evaluation of paper surface, impacts the visibility of fine detail and thus provides insight into the artistic intent of the photographer and the envisioned purpose of a particular print. For example, prints intended for reproduction or documentary functions tend to be better suited on smooth-surface papers that render details with sharpness and clarity; on the other hand, more impressionistic or expressive subjects, especially those depicting large unmodulated masses of shadows or highlights, are best suited for papers with rough, broadly open textures (Eastman Kodak Company c. 1935). 
     A result of a careful and deliberate manufacturing process, texture applied to silver gelatin paper is designed to be distinct and distinguishable through processing and post-processing procedures. Given these texture attributes, an encyclopedic collection of surface textures can reveal vital clues about a photographic print of unknown origin. Likewise a method for classifying textures can provide a means to link prints to specific photographers or to other prints of known provenance. 
     Since the composition of photographic paper was frequently changed, fake photographs are likely to be printed on modern photographic paper or photographic paper not contemporaneous with the original photograph. Therefore, there is a need for a system to non-destructively date photographic paper. 
     Determining photographic paper surface texture, a critical feature in the manufacture, marketing and use of photographic paper, is one way to non-destructively date photographic paper. Using a raking light can reveal texture through a stark rendering of highlights and shadows. Though raking light photomicrographs effectively document surface features of photographic paper, the sheer number and diversity of textures used for historic papers prohibits efficient visual classification. 
     In addition, the raking light may be applied to a sample paper with different angles of incidence and different intensities, thereby rendering different highlights and shadows for the same photograph or sample. Therefore, a need exists for a method and apparatus for standardizing and classifying photograph textures revealed by a raking light. 
     BRIEF SUMMARY 
     The foregoing and other problems are overcome, and other advantages are realized, in accordance with the presently preferred embodiments of these teachings. 
     The invention is directed towards a system for extracting texture features from a sample under investigation. The system includes a dome, wherein the dome comprises a plurality of LED rings disposed around an inner surface of the dome. The system also includes a LED controller for controlling the plurality of LEDs and the incident light impinging upon the sample situated within the dome. Also included is a CCD imager microscope and controller for capturing LED light reflected from the sample. The invention also includes a computer system for storing and analyzing the texture features from the sample. The computer system includes a processor for executing instructions; a display, operatively coupled to the processor; an input communications device; and a computer readable medium, operatively coupled to the processor. The computer readable medium contains a set of system instructions that, if executed by the processor, are operable to cause the computer system to construct a rules engine, the rules engine comprising texture identification rules and resources to classify the texture features. 
     The invention is also directed towards a system for extracting texture features from a sample under investigation. The system includes a plurality of light emitting diodes (LEDs) disposed semi-spherically around the sample, wherein the plurality of LEDs are arranged to form a plurality of LED rings and wherein each LED ring comprises a unique angle/distance pairing with respect to the sample. 
     In another embodiment the invention is directed towards a system for extracting texture features from a sample under investigation. The system includes a dome for enclosing the sample. The dome includes a plurality of light emitting diodes (LEDs) arranged to form a plurality of LED rings around the inner surface of the dome. The system also includes an LED controller for controlling the plurality of LEDs; a CCD imager microscope for capturing LED light reflected from the texture features inherent within the sample; and a charge coupled device (CCD) imager microscope controller for controlling the CCD imager microscope. In addition, the system includes a computer system for electronically storing and analyzing the texture features from the sample. The computer system includes a processor for executing instructions; a display, operatively coupled to the processor; and a computer readable medium, operatively coupled to the processor. The computer readable medium contains a set of system instructions that, if executed by the processor, are operable to cause the computer system to construct a rules engine, the rules engine comprising texture identification rules and resources to classify the texture features. The computer readable medium also contains a second set of system instructions that, if executed by the processor, are operable to cause the computer system to capture a plurality of texture datasets associated with the sample, wherein one of the plurality of texture datasets comprise a first set of texture features and a second one of the plurality of texture datasets comprise a second set of texture features. The datasets may be captured at the same time with different LED control settings and/or at different times with identical LED control settings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The subject matter which is regarded as the invention is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the invention are apparent from the following detailed description taken in conjunction with the accompanying drawings in which: 
         FIG. 1  is a pictorial illustration of a system configuration of an embodiment of the present invention; 
         FIG. 2  is a pictorial illustration of an alternate state of the system configuration of the present invention shown in  FIG. 1 ; 
         FIG. 3  is a pictorial illustration of a third alternate state of the system configuration of the present invention shown in  FIG. 1 ; and 
         FIG. 4  is a block diagram of computer architecture for implementing the system configurations shown in  FIG. 1 - FIG. 3 . 
     
    
    
     DETAILED DESCRIPTION 
     The following brief definition of terms shall apply throughout the application: 
     The term “comprising” means including but not limited to, and should be interpreted in the manner it is typically used in the patent context; 
     The phrases “in one embodiment,” “according to one embodiment,” and the like generally mean that the particular feature, structure, or characteristic following the phrase may be included in at least one embodiment of the present invention, and may be included in more than one embodiment of the present invention (importantly, such phrases do not necessarily refer to the same embodiment); 
     If the specification describes something as “exemplary” or an “example,” it should be understood that refers to a non-exclusive example; and 
     If the specification states a component or feature “may,” “can,” “could,” “should,” “preferably,” “possibly,” “typically,” “optionally,” “for example,” or “might” (or other such language) be included or have a characteristic, that particular component or feature is not required to be included or to have the characteristic. 
     Referring to  FIG. 1  there is shown a pictorial illustration of a system configuration of an embodiment of the present invention  10  for applying a raking light  17 A to a sample  11  under investigation and subsequently imaging the reflected raking light  17 B with a microscope and CCD imager  13 . The raking light  17 A is emitted from one or more LEDs  18  arranged around the perimeter of dome  14 . It will be understood that each of the LEDs may comprise a unique angle A and/or distance D from sample  11 . 
       FIG. 1  shows a single LED  16 - 1  illuminated within an array of a plurality of light emitting diodes (LEDs)  18  mounted to lighting array dome or semi-sphere  14 . It will be appreciated that any number of LEDs may be used, such as for example 48 LEDs. It will also be appreciated that the LEDs may emit any suitable color or spectrum. The lighting array dome  14  includes the plurality of LEDs coupled to the LED controller  16  through a printed circuit board (PCB). The LED controller  16  provides an inter-face to address each LED  18  and controls: illumination intensity of each LED, on/off sequence of each LED with respect to the other LEDs, and exposure or energized state time of each LED. It will be appreciated that each LED comprises a static angle and distance to a reference point, e.g., a test sample, and each LED comprises dynamic illumination intensity, exposure time, gain, and sequencing. It will also be appreciated the LEDs may be arranged geometrically such as, for example, in LED rows around the inside of the lighting array dome  14 . And, each row may comprise a unique angle/distance pair with respect to sample  11 . 
     Also shown is CCD controller  12  to control key CCD functions including image capture, white balance, image output (file creation) and gain (light sensitivity of the sensor). 
     Still referring to  FIG. 1 , an image  15  of the illuminated sample  11  is shown. As shown, the raking light  17 A illuminates the sample  11  from, in this example, an oblique angle, thus highlighting certain features of the sample  11  under investigation. 
     The dot in the graphical user interface (GUI) corresponds with the LEDs illuminated in the dome. For example, dot  16 - 1   c  corresponds to LED  16 - 1 . Each of the LEDs, can be preset for desired illuminating while examining the impact of the illumination using a preview image to determine light intensity and other camera related exposure options. Once set, the LEDs are energized in a predetermined sequence with the corresponding raking images automatically captured and save by CCD imager  13  and CCD controller  12 . It will be understood that any suitable number of LEDs may be energized. It will also be appreciated that all LED and CCD settings may be captured to precisely repeat the LED illumination. 
     Referring also to  FIG. 2  for comparison this illustration shows a different position of an illuminated LED and the corresponding dot  16 - 2   c  in the controller  16  window. Of note is the effect of the different angle of raking light illumination  24 A on the sample  11 . 
     Still referring to  FIG. 2 , an image  22  of the illuminated sample  11  is shown. As shown, the raking light  24 A illuminates the sample  11  from, in this example, a perpendicular angle, thus highlighting certain features of the sample  11  under investigation that are not readily apparent from a raking light of a different intensity or incident angle (compare item  22  with  FIG. 1 , item  15 ). 
     Referring also to  FIG. 3  for yet another comparison, this illustration shows a different position of an illuminated LED  16 - 3  and the corresponding dot  16 - 3   c  in the controller  16  window. Of note is the effect of the different angle of illumination on the sample  11  shown in image  32  (compare with  FIG. 2 , item and with  FIG. 1 , item  15 ). 
     Still referring to  FIG. 3 , an image  32  of the illuminated sample  11  is shown. The raking light from LED  16 - 3  illuminates the sample  11  from, in this example, another angle, thus highlighting certain features of the sample  11  under investigation that are not readily apparent from a raking light of a different intensity or incident angle. 
     It will be understood that the present invention advantageously provides an ability to precisely control the lighting angle and intensity and allow a repeatable way to examine and document surface features under different lighting conditions. The one or more images shown in  FIG. 1 - FIG. 3  may be captured as a texture dataset (See  FIG. 4, 414 ) for subsequent processing and comparison. For example, a texture dataset, as described herein, of a photograph, or painting, may be compared with later, or earlier captured texture datasets of the photograph or painting to determine deterioration rates, identity, and authenticity. Similarly, texture datasets, as described herein, of a painting or photograph may be compared with one or more standard texture datasets, as described herein, of known characteristics such as, for example, texture and surface composition. 
     It will be appreciated that the texture dataset of a sample described herein comprises a static or dynamic raking image. It will be understood that the static raking image is a function of the number of energized LEDs and each LED&#39;s angle and distance to the sample, and each LED&#39;s preset intensity and gain. It will be further understood that the dynamic raking image is a function of the aforementioned factors and LED exposure time and the LED&#39;s energizing or exposure sequence. 
     With reference also to  FIG. 4 , a block diagram illustrating a computer architecture  300  for LED controller  16  incidence parameters and the CCD controller  12  is shown. System  300  employs a peripheral component interconnect (PCI) local bus architecture. Although the depicted example employs a PCI bus, other bus architectures such as Accelerated Graphics Port (AGP) and Industry Standard Architecture (ISA) may be used. Processor  302  and main memory  304  are connected to PCI local bus  306  through PCI bridge  308 . PCI bridge  308  also may include an integrated memory controller and cache memory for processor  302 . Additional connections to PCI local bus  306  may be made through direct component interconnection or through add-in boards. 
     In the depicted example, local area network (LAN) adapter  310 , SCSI host bus adapter  312 , and expansion bus interface  314  are connected to PCI local bus  306  by direct component connection. It will be understood that LAN adapter  310  may also include an internet browser. In contrast, audio adapter  316 , graphics adapter  318 , and audio/video adapter  319  are connected to local bus  306  by add-in boards inserted into expansion slots. Local bus may be any suitable bus architecture such as, for example, PCI or USB. Expansion bus interface  314  provides a connection for a keyboard and mouse adapter  320 , modem  322 , and additional memory  324 . Small computer system interface (SCSI) host bus adapter  312  provides a connection for hard disk drive  326 , tape drive  328 , and CD-ROM drive  330 . Typical PCI local bus implementations will support PCI expansion slots or add-in connectors. 
     An operating system runs on processor  302  and is used to coordinate and provide control of various components within data processing system  31 . Data processing sa processing system  31  may be configured to process dataset  414  as described herein. The operating system may be any suitable commercially available operating system. In addition, an object oriented programming system such as Java may run in conjunction with the operating system and provide calls to the operating system from Java programs or applications executing on data processing system  300 . “Java” is a trademark of Sun Microsystems, Inc. Instructions for the operating system, the object-oriented operating system, and applications or programs are located on storage devices, such as hard disk drive  326 , and may be loaded into main memory  304  for execution by processor  302 . 
     System  300  may be configured to regressively cluster texture dataset  414  to allocate data points within the dataset to a probable date range or a comparison confidence factor. In some embodiments, such an adaptation may be incorporated within system  300 . In particular, system  300  may include storage medium  324  with program instructions  413  executable by processor  302  to regressively cluster dataset  414 . In an embodiment in which dataset  414  is external to system  300 , however, the adaptation to regressively cluster dataset  414  may be additionally, or alternatively, incorporated within the respective data source/s of dataset  414 . In particular, the data source/s of dataset  414 , in such an embodiment, may include a storage medium with program instructions which are executable through a processor for regressively clustering data. 
     In general, input may be transmitted to system  300  to execute program instructions  413  within storage medium  324 . Storage medium  324  may include any device for storing program instructions, such as, for example, a read-only memory, a random access memory, a magnetic or optical disk, or a magnetic tape. Program instructions  413  may include any instructions by which to perform any suitable method or regression clustering and classification processes. In particular, program instructions  413  may include instructions for correlating variable parameters of a dataset and other instructions for clustering the dataset through the iteration of a regression algorithm. In this manner, program instructions  413  may used to generate a plurality of different functions correlating variable parameters of a dataset. 
     In addition, program instructions  413  may include instructions for determining directives by which to classify new data into the dataset with respect to the generated functions. In some cases, program instructions  13  may further include instructions by which to receive new data and predict values of variable parameters associated with the new data and dataset. 
     For example, the computer readable medium may contain a set of system instructions that, if executed by the processor  302 , are operable to cause the computer system  300  to capture a plurality of texture datasets associated with the sample  11 ; where each of the texture datasets may be captured at different times or under different conditions. In this manner the comparisons may be used to determine degradation or authenticity. 
     Similarly, the computer readable medium may contain a set of system instructions that, if executed by the processor  302 , are operable to cause the computer system  300  to generate a baseline texture dataset. The baseline texture dataset may be generated according to a predetermined formula or determined empirically with a sample having known characteristics. 
     Those of ordinary skill in the art will appreciate that the hardware in  FIG. 1  through  FIG. 4  may vary depending on the implementation. Other internal hardware or peripheral devices, such as flash read-only memory (ROM), equivalent nonvolatile memory, or optical disk drives and the like, may be used in addition to or in place of the hardware depicted in  FIG. 1 - FIG. 4 . 
     The depicted example in  FIG. 1 - FIG. 4  and above-described examples are not meant to imply architectural limitations. For example, system  300  also may be a notebook computer or hand held computer in addition to taking the form of a PDA. 
     It should be understood that the foregoing description is only illustrative of the invention. Thus, various alternatives and modifications can be devised by those skilled in the art without departing from the invention. Accordingly, the present invention is intended to embrace all such alternatives, modifications and variances that fall within the scope of the appended claims.

Technology Classification (CPC): 6