Abstract:
Image processing method and apparatus of same are provided. An image processing method includes a first step of processing first image data obtained by capturing an image of a predetermined region including a blood vessel pattern of a biological entity so as to enhance the image corresponding to the blood vessel pattern in the first image data to generate second image data; a second step of processing each pixel data composing the second pixel data generated at the first step to generate index data indicating an average value of pixel data of pixels around a pixel corresponding to the pixel data or a value obtained by leveling pixel data of the surrounding pixels; and a third step of subtracting the index data generated at the second step corresponding to the pixel data from each pixel data composing the second image data generated at the first step to generate third image data.

Description:
CROSS REFERENCES TO RELATED APPLICATIONS  
       [0001]     The present application claims priority to Japanese Patent Application No. 2004-235270 filed in the Japan Patent Office on Aug. 12, 2004, the entire contents of which being incorporated herein by reference.  
       BACKGROUND  
       [0002]     The present invention relates to an image processing method and apparatus for generating an image suitable for identification based on a blood vessel pattern of a biological entity.  
         [0003]     The blood vessel pattern of a human finger and the like is unique to the individual. Therefore, there are identification systems for identifying users based on blood vessel patterns. Such identification systems extract blood vessel pattern data from image data obtained by capturing an image of the finger of the user and compare the extracted blood vessel pattern data and previously held blood vessel pattern data for identification.  
         [0004]     The above-mentioned identification systems, however, have a problem in that captured image includes images of patterns other than the blood vessel pattern or false images, so the precision of extraction of the blood vessel pattern data is low and practical application is difficult.  
       SUMMARY  
       [0005]     The present invention is provides in an embodiment an image processing method and apparatus able to extract data concerning a blood vessel pattern of a biological entity with a high precision and generate image data from the same.  
         [0006]     To solve the problem in the related art, according to a first aspect of the invention, there is provided an image processing method including a first step of processing first image data obtained by capturing an image of a predetermined region including a blood vessel pattern of a biological entity so as to enhance the image corresponding to the blood vessel pattern in the first image data to generate second image data; a second step of processing each pixel data composing the second pixel data generated at the first step to generate index data indicating an average value of pixel data of pixels around a pixel corresponding to the pixel data or a value obtained by leveling pixel data of the surrounding pixels; and a third step of subtracting the index data generated at the second step corresponding to the pixel data from each pixel data composing the second image data generated at the first step to generate third image data.  
         [0007]     According to a second aspect of the invention, there is provided an image processing apparatus comprising an enhancing means for processing first image data obtained by capturing an image of a predetermined region including a blood vessel pattern of a biological entity so as to enhance the image corresponding to the blood vessel pattern in the first image data to generate second image data; an index generating means for processing each pixel data composing the second pixel data generated at the enhancing means to generate index data indicating an average value of pixel data of pixels around a pixel corresponding to the pixel data or a value obtained by leveling pixel data of the surrounding pixels; and a reducing means for subtracting the index data generated at the index generating means corresponding to the pixel data from each pixel data composing the second image data generated at the enhancing means to generate third image data.  
         [0008]     According to a third aspect of the invention, there is provided an image processing apparatus including an enhancing circuit for processing first image data obtained by capturing an image of a predetermined region including a blood vessel pattern of a biological entity so as to enhance the image corresponding to the blood vessel pattern in the first image data to generate second image data; an index generating circuit for processing each pixel data composing the second pixel data generated at the enhancing circuit to generate index data indicating an average value of pixel data of pixels around a pixel corresponding to the pixel data or a value obtained by leveling pixel data of the surrounding pixels; and a reducing circuit for subtracting the index data generated at the index generating circuit corresponding to the pixel data from each pixel data composing the second image data generated at the enhancing circuit to generate third image data.  
         [0009]     Additional features and advantages are described herein, and will be apparent from, the following Detailed Description and the figures.  
     
    
     BRIEF DESCRIPTION OF THE FIGURES  
       [0010]      FIG. 1  is a view of the configuration of an identification apparatus of an embodiment of the present invention.  
         [0011]      FIG. 2  is a view for explaining image data after clipping input to a noise elimination unit.  
         [0012]      FIGS. 3A and 3B  are views for explaining image data before and after processing of the noise elimination unit shown in  FIG. 1 .  
         [0013]      FIG. 4  is a flow chart for explaining an example of the operation of a vein clarifying unit shown in  FIG. 1 .  
         [0014]      FIGS. 5A  to  5 C are views for explaining image data processed by the vein clarifying unit shown in  FIG. 1 .  
         [0015]      FIG. 6  is a flow chart for explaining the processing of a peripheral average brightness subtraction unit shown in  FIG. 1 .  
         [0016]      FIGS. 7A and 7B  are views for explaining the processing of the peripheral average brightness subtraction unit shown in  FIG. 1 .  
         [0017]      FIGS. 8A and 8B  are views for explaining the image data before and after the processing of the peripheral average brightness subtraction unit shown in  FIG. 1 .  
         [0018]      FIGS. 9A and 9B  are views for explaining the image data before and after the processing of a vein extraction unit shown in  FIG. 1 .  
         [0019]      FIG. 10  is a flow chart for explaining an example of the entire operation of the identification apparatus shown in  FIG. 1 . 
     
    
     DETAILED DESCRIPTION  
       [0020]     Preferred embodiments of the present invention will be described in detail below while referring to the attached figures.  
         [0021]      FIG. 1  is a view of the configuration of an identification apparatus  1  of an embodiment of the invention. As shown in  FIG. 1 , the identification apparatus  1  has for example a clipping portion  12 , noise elimination unit  14 , vein clarifying unit  16 , peripheral average brightness subtraction unit  18 , vein extraction unit  20 , and identification unit  22 . Each of the clipping portion  12 , noise elimination unit  14 , vein clarifying unit  16 , peripheral average brightness subtraction unit  18 , vein extraction unit  20 , and identification unit  22  is realized by for example dedicated hardware or by executing a predetermined program in a processing circuit.  
         [0022]     Below, the components shown in  FIG. 1  will be explained in detail.  
         [0023]     Clipping Portion  12   
         [0024]     The clipping portion  12  receives as input identified image (captured image) data RD obtained by capturing an image of a finger of a person being identified (with a vein pattern), clips image data S 12  corresponding to the finger vein extraction range from the identified image data RD, and outputs the same to the noise elimination unit  14 . Due to this, the effects exerted upon the identification processing by images of portions other than the finger in the identified image data RD can be eliminated. The image in accordance with the identified image data RD becomes for example as shown in  FIG. 2 , while the image data S 12  after clipping becomes for example as shown in  FIG. 3A .  
         [0025]     Noise Elimination Unit  14   
         [0026]     The noise elimination unit  14  eliminates the noise from the image data S 12  input from the clipping portion  12  to generate the image data S 14  and outputs this to the vein clarifying unit  16 . The noise elimination unit  14  performs for example median filtering to eliminate noise. The median filtering arranges the brightness data of pixels in for example a predetermined region in order from the smallest data and allocates the brightness data located at the center as the brightness data at the center of the predetermined region. Due to this, the effects due to the image of dust etc. in the image data S 12  can be eliminated. The image in accordance with the image data S 14  becomes for example as shown in  FIG. 3B .  
         [0027]     Vein Clarifying Unit  16   
         [0028]     The vein clarifying unit  16  performs processing for enhancing (clarifying) the vein pattern in the image data S 14  to generate the image data S 16  and outputs this to the peripheral average brightness subtraction unit  18 .  FIG. 4  is a flow chart for explaining the processing of the vein clarifying unit  16  shown in  FIG. 1 .  
         [0029]     Step ST 1   
         [0030]     The vein clarifying unit  16  enters the image data S 14  after the noise elimination input from the noise elimination unit  14  for the variable dnI.  
         [0031]     Step ST 2   
         [0032]     The vein clarifying unit  16  generates differentiated image data diff (dnI) of the variable dnI (first data of the present invention).  
         [0033]     At this time, the vein clarifying unit  16  differentiates the brightness value of the image entered for the variable dnI. The vein clarifying unit  16  adds the variable dnI to the data generated by multiplying an absolute value abs(diff(dnI)) of the differentiated image data diff(dnI) by n (for example 10) (second data of the present invention) to calculate a variable s (third data of the present invention). The vein clarifying unit  16  differentiates the value using a differentiation operator not including self-contradictions disclosed in for example  Transactions of Society of Instrument and Control Engineers , vol. 40, no. 11, Jan. 7, 2001, “Numerical Partial Differentiation Operators not Including Self-Contradictions and Application of Same”, Shigeru Ando”. The vein clarifying unit  16  uses for example the operator shown in the following Equation (1) as a 5×5 differentiation operator F:  
             F   =     [           -   0.003776           -   0.010199         0       0.010199       0.003776             -   0.026786           -   0.070844         0       0.070844       0.026786             -   0.046548           -   0.122572         0       0.122572       0.046548             -   0.026786           -   0.070844         0       0.026786       0.070844             -   0.003776           -   0.010199         0       0.010199       0.003776                   (   1   )             
 
         [0034]     In the present embodiment, the vein clarifying unit  16  can clarify the veins with a high precision by differentiation.  
         [0035]     Step ST 3   
         [0036]     The vein clarifying unit  16  enters an initial value “1” for the variable i.  
         [0037]     Step ST 4   
         [0038]     The vein clarifying unit  16  calculates the differentiated image data diff(s) of the variable s calculated at step ST 2 , adds the absolute value abs(diff(s)) thereof to the variable s, and defines this as a new variable s.  
         [0039]     Step ST 5   
         [0040]     The vein clarifying unit  16  judges whether or not the variable i is smaller than a predetermined threshold value m. When judging it is smaller, the routine proceeds to step ST 6 , while when judging not, the routine proceeds to step ST 7 . Namely, the vein clarifying unit  16  repeats the processing of step ST 4  m number of times (for example 4 times) to clarify the vein pattern.  
         [0041]     Step ST 6   
         [0042]     The vein clarifying unit  16  increments the variable i by exactly “1”.  
         [0043]     Step ST 7   
         [0044]     The vein clarifying unit  16  subtracts the variable s from a predetermined value “255” and defines the result as a new variable s.  
         [0045]     Step ST 8   
         [0046]     The vein clarifying unit  16  divides each of the pixel data composing the variable s newly generated at step ST 7  by the highest brightness value max(s)x among the pixel data composing the variable s and enters the result for the variable s. Then, the vein clarifying unit  16  outputs the finally generated variable s as the image data S 16  to the peripheral average brightness subtraction unit  18 .  
         [0047]     Here, an image in accordance with the absolute value abs(diff(dnI)) of the differentiated image data diff(dnI) of step ST 2  shown in  FIG. 4  becomes for example as shown in  FIG. 5A . Further, the image in accordance with the variable s generated at step ST 2  becomes for example as shown in  FIG. 5B . Further, the image in accordance with the variable s generated at step ST 8  becomes for example as shown in  FIG. 5C .  
         [0048]     Peripheral Average Brightness Subtraction Unit  18   
         [0049]     The peripheral average brightness subtraction unit  18  processes each of the pixel data composing the image data S 16  input from the vein clarifying unit  16  to generate index data x indicating an average value of brightness values indicated by the pixel data of pixels at the periphery of the pixel corresponding to that pixel data or a value obtained by leveling the brightness values indicated by the pixel data of the peripheral pixels. In the following example, a case where the average value ave(i,j) is used as the index data x is exemplified. Then, the peripheral average brightness subtraction unit  18  subtracts the index data x from each pixel data composing the image data S 16  to generate the image data S 18 .  
         [0050]      FIG. 6  is a flow chart for explaining the processing of the peripheral average brightness subtraction unit  18 .  
         [0051]     Step ST 11   
         [0052]     The peripheral average brightness subtraction unit  18  selects an unprocessed pixel among the pixels corresponding to the pixel data composing the image data S 16  input from the vein clarifying unit  16  and selects a brightness value s(i,j) indicated by the pixel data corresponding to the selected pixel for processing. Here, i and j indicate numbers in the x- and y-directions in the pixel region corresponding to the image data S 16 .  
         [0053]     Step ST 12   
         [0054]     The peripheral average brightness subtraction unit  18  calculates the average value ave(i,j) of the brightness values indicated by the pixel data corresponding to the pixels in the predetermined region located at the periphery of the pixel selected at step ST 11 . The peripheral average brightness subtraction unit  18  processes for the pixel (i,j) in the region corresponding to the image data S 16  for example as shown in  FIG. 7A  to calculate the average value ave(i,j) of the brightness values indicated by the image data of (2d+1) 2  pixels in a rectangular area AREA(i,j) having a distance d for each of an x plus direction, an x minus direction, a y plus direction, and a y minus direction with respect to the pixel (i,j) as shown in  FIG. 7B . The processing for calculating the average value ave(i,j) is indicated by the following Equation (2).  
               ave   ⁡     (     i   ,   j     )       =         ∑     v   =     j   -   d         j   +   d       ⁢       ∑     u   =     i   -   d         i   +   d       ⁢     s   ⁡     (     u   ,   v     )               (       2   ⁢   d     +   1     )     2               (   2   )             
 
         [0055]     Step ST 13   
         [0056]     The peripheral average brightness subtraction unit  18  subtracts the average value ave(i,j) calculated at step ST 12  from the brightness value s(i,j) indicated by each pixel data composing the brightness data S 16  to calculate a new brightness value s(i,j).  
         [0057]     Step ST 14   
         [0058]     The peripheral average brightness subtraction unit  18  judges whether or not the selection at step ST 11  was carried out for all pixel data composing the image data S 16 . When judging that the selection was not carried out, the routine returns to step ST 11 , while when judging that the selection was carried out, the processing ends. The peripheral average brightness subtraction unit  18  outputs the image data S 18  comprised of the new brightness value s(i,j) to the vein extraction unit  20 . According to the above-mentioned processing, image data S 18  shown in  FIG. 8B  in which the vein pattern is clarified is generated based on the image data S 16  shown in  FIG. 8A .  
         [0059]     Vein Extraction Unit  20   
         [0060]     The vein extraction unit  20  calculates an average brightness value M of all pixel data composing the image data S 18 . Then, the vein extraction unit  20  judges whether or not the brightness value indicated by the pixel data is larger than the average brightness value M for each of all of the pixel data composing the image data S 18  input at step ST 13 . When judging that the brightness value is larger, the brightness value is maintained at it is, while when judging that the brightness value is not larger, the brightness value of the pixel data is made zero and new image data S 20  is generated. By the above-mentioned processing, the image data S 20  shown in  FIG. 9B  obtained by further clarifying the vein pattern is generated based on the image data S 18  shown in  FIG. 9A .  
         [0061]     Identification Unit  22   
         [0062]     The identification unit  22  compares the image data S 18  input from the peripheral average brightness subtraction unit  18  and vein pattern data REF previously stored for identification and judges whether or not the person being identified is legitimate.  
         [0063]     Below, an example of the overall operation of the identification apparatus  1  shown in  FIG. 1  will be explained.  FIG. 10  is a flow chart for explaining an example of the overall operation of the identification apparatus  1  shown in  FIG. 1 .  
         [0064]     Step ST 21   
         [0065]     The clipping portion  12  receives as input the identified image (imaging image) data RD obtained by capturing an the finger of the person being identified, clips the image data S 12  corresponding to the finger vein extraction range in identified image data RD, and outputs the same to the noise elimination unit  14 .  
         [0066]     Step ST 22   
         [0067]     The noise elimination unit  14  eliminates the noise from the image data S 12  input from the clipping portion  12  at step ST 21  to generate the image data S 14  and outputs this to the vein clarifying unit  16 .  
         [0068]     Step ST 23   
         [0069]     The vein clarifying unit  16  performs the processing explained by using  FIG. 4  for enhancing (clarifying) the vein pattern in the image data S 14  input from the noise elimination unit  14  at step ST 22  to generate the image data S 16  and outputs this to the peripheral average brightness subtraction unit  18 .  
         [0070]     Step ST 24   
         [0071]     The peripheral average brightness subtraction unit  18 , as explained by using  FIG. 6 , processes each of the pixel data composing the image data S 16  input from the vein clarifying unit  16  at step ST 23  to generate an index data x indicating the average value of brightness values indicated by the pixel data of pixels at the periphery of the pixel corresponding to that pixel data or the value obtained by leveling the brightness values indicated by the pixel data of the peripheral pixels. Then, the peripheral average brightness subtraction unit  18  subtracts the index data x from each pixel data composing the image data S 16  to generate the image data S 18 .  
         [0072]     Step ST 25   
         [0073]     The vein extraction unit  20  calculates the average brightness value M of all pixel data composing the image data S 18  input at step ST 24 . Then, the vein extraction unit  20  processes each of all pixel data composing the image data S 18  input at step ST 13  to judge whether or not the brightness value indicated by the pixel data is larger than the average brightness value M, maintains the brightness value of the pixel data judged to be large as it is, reduces to zero the brightness value of the pixel data judged not to be large, and generates new image data S  20 .  
         [0074]     Step ST 26   
         [0075]     The identification unit  22  compares the image data S 18  input from the peripheral average brightness subtraction unit  18  at step ST 25  with the vein pattern data REF stored previously for the identification and judges whether or not the person being identified is legitimate.  
         [0076]     As explained above, according to the identification apparatus  1 , as explained by using  FIG. 6 , the peripheral average brightness subtraction unit  18  processes each of the pixel data composing the image data S 16  to generate index data x indicating the average value of brightness values indicated by the pixel data of pixels at the periphery of the pixel corresponding to that pixel data or the value obtained by leveling the brightness values indicated by the pixel data of the peripheral pixels. Then, the peripheral average brightness subtraction unit  18  subtracts the index data x from each of the pixel data composing the image data S 16  to generate the image data S 18 . By this, it is possible to generate image data S 18  from which false images or images other than the vein pattern included in the image data S 16  have been suitably removed and possible to enhance the precision of identification at the identification unit  22 .  
         [0077]     Further, according to the identification apparatus  1 , the vein clarifying unit  16  shown in  FIG. 1  performs the vein clarifying processing as explained by using  FIG. 4 . By this, it is possible to perform the above-mentioned processing in the peripheral average brightness subtraction unit  18  with a high precision.  
         [0078]     The present invention is not limited to the embodiment explained above. In the above embodiment, as the enhancing processing of the present invention, the processing explained by using  FIG. 4  was exemplified, but other enhancing processing may be used as well so far as it is processing for enhancing the vein pattern.  
         [0079]     The present invention can be applied to a system for identification based on a blood vessel pattern.  
         [0080]     Note that at least one of the clipping portion  12 , noise elimination unit  14 , the vein clarifying unit  16 , the peripheral average brightness subtraction unit  18 , the vein extraction unit  20 , and the identification unit  22  may be realized by a circuit or a program executed by a computer.  
         [0081]     Each of the clipping portion  12 , noise elimination unit  14 , vein clarifying unit  16 , peripheral average brightness subtraction unit  18 , vein extraction unit  20 , and identification unit  22  is realized by for example dedicated hardware or by executing a predetermined program in a processing circuit.  
         [0082]     It should be understood by those skilled in the art that various modifications, combinations, sub-combinations, and alterations may occur depending on design requirements and other factors insofar as they are within the scope of the appended claims or the equivalents thereof.  
         [0083]     It should be understood that various changes and modifications to the presently preferred embodiments described herein will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present subject matter and without diminishing its intended advantages. It is therefore intended that such changes and modifications be covered by the appended claims.