Abstract:
An image processing apparatus connectable to a terminal through a network, includes a receiver configured to receive original image data uploaded from the terminal, an image processor configured to change a tone of the original image data, a transmitter which transmits tone-changed image data output from the image processor to the terminal, and a face detector configured to detect a face region in the original image data received by the receiver, wherein the image processor is configured to perform a first tone-change for image data of the face region in the original image data, and perform a second tone-change for image data of another region in the original image data.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is based upon and claims the benefit of priority from prior Japanese Patent Applications No. 2011-078900, filed Mar. 31, 2011; and No. 2011-280552, filed Dec. 21, 2011, the entire contents of all of which are incorporated herein by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    1. Field of the Invention 
         [0003]    The present invention relates to an image processing apparatus, an image processing method, and a storage medium, which process a photographic image including a person, with varied conversion degree of a face region of the person, when the photographic image is converted into a painting image. 
         [0004]    2. Description of the Related Art 
         [0005]    In recent years, people have enjoyed photographs in increasingly various ways, with spread of digital cameras. In particular, since image data of digital cameras are digital image data, various image processing can be performed. 
         [0006]    For example, a technique of generating and displaying an image featuring a different tone (such as a painting image) based on an original photograph, by adding image processing to the original photograph, has been proposed (for example, see Jpn. Pat. Appin. KOKAI Publication No. 8-44867). 
         [0007]    By developing the technique of Jpn. Pat. Appin. KOKAI Publication No. 8-44867, it has been proposed to extract characteristics such as color information and stroke information from an image of a picture which is actually drawn by a painter, providing a taken photograph with the extracted characteristics, and thereby converting the photograph into an artistic painting image in consideration of the whole original image (for example, see Jpn. Pat. Appin. KOKAI Publication No. 2004-213598). 
         [0008]    Besides, a technique of converting the photograph by changing the image tone such as pictorial tone has been proposed (for example, see Jpn. Pat. Appin. KOKOU Publication No. 1-46905). 
         [0009]    In addition, it has been proposed to perform tone change such as pictorial tone in a network service site, to which a terminal can be connected through the 
         [0010]    Internet (for example, see Jpn. Pat. Appin. KOKAI Publication No. 2011-243187). 
         [0011]    However, when a photograph is converted into a painting image, photographs of scenery, flowers, and buildings can be artistic even when they are subjected to bold tone change. Photographs of human faces, however, have the problem of having unnatural appearance when they are subjected to extreme change. 
         [0012]    In addition, image data which are subjected to tone change have the problem that unnaturalness of the human faces becomes more conspicuous in the printed image data. 
       BRIEF SUMMARY OF THE INVENTION 
       [0013]    An object of the present invention is to provide an image processing apparatus, an image processing method and a storage medium, in which a region of a human face is detected and different tone changes are performed for the face region and other regions, and thereby human faces can be expressed with natural impression. 
         [0014]    According to one embodiment of the present invention, an image processing apparatus connectable to a terminal through a network, includes a receiver configured to receive original image data uploaded from the terminal; an image processor configured to change a tone of the original image data; a transmitter which transmits tone-changed image data output from the image processor to the terminal; and a face detector configured to detect a face region in the original image data received by the receiver, wherein the image processor is configured to perform a first tone-change for image data of the face region in the original image data, and perform a second tone-change for image data of another region in the original image data. 
         [0015]    According to another embodiment of the present invention, an image processing apparatus includes a designating module configured to designate a tone; an image processor which converts a tone of original image data into the tone designated by the designating module; and a face detector configured to detect a face region in the original image data, wherein the image processor is configured to perform a first tone-change for image data of the face region in the original image data, and perform a second tone-change for image data of another region in the original image data. 
         [0016]    Additional objects and advantages of the present invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present invention. 
         [0017]    The objects and advantages of the present invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out hereinafter. 
         [0018]    According to the present invention, when a photograph image including a person is converted into an image of a predetermined tone such as a painting tone, unnaturalness of the whole image is removed, and tone conversion which expresses human faces naturally can be realized. 
     
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         [0019]    The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present invention and, together with the general description given above and the detailed description of the embodiments given below, serve to explain the principles of the present invention. 
           [0020]      FIG. 1  is a block diagram illustrating a configuration of a network system of an image processing system according to an embodiment of the present invention. 
           [0021]      FIG. 2  is a diagram illustrating an example of a terminal according to the embodiment. 
           [0022]      FIG. 3  is a functional block diagram illustrating a schematic structure of the terminal according to the embodiment. 
           [0023]      FIG. 4  is a diagram illustrating a tone selection menu of the terminal according to the embodiment. 
           [0024]      FIG. 5  is a block diagram illustrating a schematic structure of a server according to the embodiment. 
           [0025]      FIG. 6  is a diagram illustrating attribute information of a user ID according to the embodiment. 
           [0026]      FIG. 7  is a diagram illustrating attribute information of an image ID according to the embodiment. 
           [0027]      FIG. 8  is a process diagram illustrating exchange of data between the terminal and the server according to the embodiment. 
           [0028]      FIG. 9  is a flowchart for explaining image converting processing according to the embodiment. 
           [0029]      FIGS. 10A ,  10 B,  10 C,  10 D, and  10 E are diagrams for explaining fineness in the image converting processing. 
           [0030]      FIGS. 11A and 11B  are diagrams for explaining a shape of a stroke in the image converting processing. 
           [0031]      FIG. 12  is a flowchart for explaining face detection processing according to the embodiment. 
           [0032]      FIG. 13  is a diagram for explaining face region creation according to the embodiment. 
           [0033]      FIGS. 14A and 14B  are diagrams for explaining a face region map. 
           [0034]      FIGS. 15A ,  15 B,  15 C, and  15 D are diagrams for explaining image conversion using the face region map. 
           [0035]      FIG. 16  is a diagram for explaining a boundary of the face region. 
           [0036]      FIG. 17  is a flowchart for explaining download of an artwork in the embodiment. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0037]    The embodiments of the present invention will be described below with reference to drawings. 
       First Embodiment 
       [0038]      FIG. 1  is a block diagram showing the configuration of a network of an image processing system according to an embodiment of the present invention. 
         [0039]    An image service site  10  with a social network service function is connected to terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . via a network such as the Internet  500 . The image service site  10  includes a server  11  which stores image data (mainly image data of a photo shot by a digital camera) uploaded from a user via the terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . , converts the uploaded image into painting image, and also allows other users to browse the uploaded image and the converted painting image. The image service site  10  further includes a printer  12  which prints the converted painting image on a print medium in response to a request from the user. The printer  12  may not be located in the image service site  10 , but be located in other sites which provide a print service. 
         [0040]    The terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . may be an ordinary personal computer or mobile phone which has a communication function or an image display function. 
         [0041]      FIG. 2  is a diagram illustrating an example of the terminal  1 - 1  which can access the image service site  10 , more specifically, a smart phone which is a so-called multi-function mobile phone terminal. As illustrated in  FIG. 2 , the terminal  1 - 1  includes a comparatively large display screen  84   a,  which can display a desired image  91 . 
         [0042]      FIG. 3  is a functional block diagram illustrating a schematic structure of the terminal  1 - 1 . A camera  81  which is not shown in  FIG. 2  is provided on a back surface of the terminal  1 - 1 . The camera  81  functions to shoot a desired subject and obtain image data thereof. 
         [0043]    A transmitter  82  functions to upload image data of a photograph taken by the camera  81  onto the server  11  when necessary. 
         [0044]    A receiver  83  functions to receive control data which is transmitted from the server  11 , and painting image data which is obtained by image converting processing performed by the server  11 . 
         [0045]    A display  84  functions to display an image taken by the camera  81 , or a painting image based on painting image data that is downloaded from the server  11  by the receiver  83 , on the display screen  84   a  illustrated in 
         [0046]      FIG. 2 . The display screen  84   a  also functions as a touch panel, and displays various operation menus. 
         [0047]    The operation menus include a tone selection menu  801 , in which a plurality of tone selection buttons  801   a,    801   b,    801   c,  . . . are arranged to enable the user to select a desired tone, as illustrated in  FIG. 4 . 
         [0048]    A storage module  85  mainly functions to store image data of images taken by the camera  81 , and painting image data that is downloaded from the server  11 . 
         [0049]    A display controller  86  functions to cause the display  84  to display an image or an operation menu, in accordance with a predetermined display control program. 
         [0050]    A communication controller  87  functions to cause the transmitter  82  and the receiver  83  to perform data communication such as upload and download of image data, in accordance with a predetermined communication program. 
         [0051]    An operation controller  88  functions to detect a touch position of the display screen  84   a  (touch panel) by the user, specify the instruction of the user, and supply the specified instruction to the display controller  86  and/or the communication controller  87 . 
         [0052]      FIG. 5  is a block diagram showing principal portions in the configuration of the server  11  included the image service site  10 . The server  11  is provided with a member area  100 , a common area  200 , and a control area  300 . 
         [0053]    The member area  100  is an area provided for each registered member and stores a user ID  102  to identify each member and various kinds of attribute information  104  for each user corresponding thereto. 
         [0054]    The attribute information  104  is, as shown in  FIG. 6 , user-specific information including the name, handle name, gender, age, region, membership type, and others. The membership type includes a free member registered without charge, a pay member registered on a chargeable basis, and a premium member who pays a special membership fee (for example, an annual membership fee). 
         [0055]    The member area  100  includes an uploaded image buffer  106  which stores image data of photos uploaded by the user, an artwork memory  108  which stores painting images (artworks) obtained through snapshot-to-painting conversion by the server  11 , and a downloaded artwork memory  110  which stores artworks of other users downloaded from the other users. 
         [0056]    The common area  200  is an area provided commonly to all users and includes an artwork area  202  which stores many artworks obtained by snapshot-to-painting conversion of images uploaded by the users. 
         [0057]    Each artwork stored in the artwork area  202  has image data  208  stored together with an image ID  204  to identify the artwork and attribute information  206  of the artwork. 
         [0058]    The attribute information  206  includes, as shown in  FIG. 7 , the user ID indicating a contributor of the artwork, date information such as the creation date or posting date, size of image data, image type information such as the type of painting tone, access count information indicating the number of times the artwork is browsed, download count information indicating the number of times the artwork is downloaded, point information indicating evaluation of the artwork, and other information specific to artworks. The creator of the artwork is known from the user ID and whether the creator is a pay member or premium member can be identified. 
         [0059]    In the present embodiment, artworks are not displayed uniformly and instead, the display manner can be changed based on the “value” thereof. Examples of the value include the point number, which is attribute information attached to each artwork, access count, and download count, and the membership type of the creator of each artwork. 
         [0060]    The control area  300  includes a snapshot-to-painting conversion processor  302 , a parameter table  304 , a face region map  306 , a display controller  308 , an evaluation controller  310 , a membership management unit  312 , a face detector  314 , and a print controller  316 . 
         [0061]    The snapshot-to-painting conversion processor  302  performs snapshot-to-painting conversion processing that converts image data stored in the artwork memory  108  into painting image data. The face detector  314  detects a face region of an arbitrary person in the image data stored in the artwork memory  108 . The parameter table  304  stores parameters for snapshot-to-painting conversion referenced by the snapshot-to-painting conversion processor  302  to perform the snapshot-to-painting conversion processing. The face region map  306  stores data indicating a face region in the image and for snapshot-to-painting conversion referenced by the snapshot-to-painting conversion processor  302  to perform the snapshot-to-painting conversion processing. The display controller  308  stores a control program that causes a screen of the terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . to display artworks. 
         [0062]    The evaluation controller  310  evaluates artworks stored in the artwork memory  108  of the member area  100  based on the access count or the like and attaches a point to each artwork. The membership management unit  312  manages members based on the user ID and controls services separately for free members, pay members, and premium members. The membership management unit  312  also administers the social network service function of the server  11 . The print controller  316  performs a print operation for an artwork by the printer  12 . 
         [0063]    The server  11  is provided with a CPU  20 , a display buffer  30 , and a communication unit  40 . The CPU  20  controls the whole server  11  (each unit described above) and also performs various kinds of processing needed to display many artworks at a glance on the Internet. 
         [0064]    The CPU  20  also performs an operation accompanied with a snapshot-to-painting conversion by the snapshot-to-painting conversion processor  302 . The display buffer  30  is a work memory to generate images for the display when the CPU  20  causes a display screen to display many artworks at a glance. The communication unit  40  performs a communication processing for data transmission/reception according to an operation of the CPU  20  between the terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . . 
         [0065]    Concrete operations of an image processing system according to the present embodiment will be described below with reference to flow charts. 
         [0066]    First, processes when an image is uploaded, displayed, browsed, and downloaded between the terminals  1 - 1 ,  1 - 2 ,  1 - 3 , . . . and the server  11  on the image service site  10  will be described with reference to  FIG. 8 . 
         [0067]    If the user is a member (a free member, pay member, or premium member), the user accesses the server  11  from the terminal of the user (step SB 1 ). The server  11  authenticates the user ID after the user being logged in (step SC 1 ) and, if it is verified that the user is a member, sends a page of the member so that the user can view the page (step SC 2 ). 
         [0068]    When the page of the member is opened, the member uploads an image (step SB 2 ). The uploaded image is received by the receiver  40  and stored in the uploaded image buffer  106  of the member area  100  of the server. If the member request a snapshot-to-painting conversion of the image (step SB 3 ), the server  11  performs the snapshot-to-painting conversion processing (or image converting processing) (step SC 3 ) and the converted image, that is, the artwork is stored in the artwork memory  108 . 
         [0069]    If the user uses the terminal  1 - 1  shown in  FIG. 2  to request the server of a snapshot-to-painting conversion at step SB 3 , the user performs a predetermined operation to display the tone selection menu  801  on the display of the terminal  1 - 1 . The user can select a desired tone on the tone selection menu  801 . Information indicating the selected tone is transmitted to the server  11  from the terminal  1 - 1  as the tone to be converted. 
         [0070]    An artwork which is a tone-converted image obtained by the server  11  is transmitted from the server  11  to the terminal  1 - 1  of the user and displayed on the terminal  1 - 1 . 
         [0071]    If the user requests a print operation of the artwork (tone-converted image) at step SB 4 , the tone-converted image data stored in the artwork memory  108  is transmitted to the printer  12  from the server  11  by the communication unit  40  and is printed (SC 4 ). At step SC 4 , an artwork is printed on a predetermined print medium based on the painting data (tone-converted image data). The print medium is delivered to the user by an offline manner. 
         [0072]    The member may personally enjoy the converted artwork, but may post the artwork if the artwork is desired to be released to other users (step SB 5 ). The posted artwork is transferred from the artwork memory  108  of the member area  100  to the artwork area  202  of the common area  200  and stored there. Incidentally, the attribute information  206  as described with reference to  FIG. 7  is attached each artwork in the artwork area  202 . 
         [0073]    The server  11  displays artworks in the artwork area  202  at a glance if necessary (step SC 5 ). Incidentally, the server  11  resizes artworks in the artwork area  202  when displaying artworks at a glance if appropriate. That is, because the size of artworks in the artwork area  202  is normally larger than the image size for display at a glance, the artworks are reduced and if the size of artworks in the artwork area  202  is smaller than the image size for display at a glance, the artworks are enlarged. 
         [0074]    The member can browse any artwork displayed at a glance in an actual size by making a request of browsing (step SB 6 ). If a browsing request is made, the server  11  displays the requested artwork in the original size (step SC 6 ) and also adds up a point to the artwork whose browsing is requested (step SC 7 ). 
         [0075]    The member may press a GOOD button displayed in the page of the member and indicating that the browsed artwork suits his (her) taste or write a comment such as his (her) impressions (step SB 7 ). If the GOOD button is pressed or a comment such as impressions is written, the server  11  adds up a point to the browsed artwork (step SC 7 ). The evaluation of the artwork is thereby raised. It is assumed that the point number of comment writing is higher than the point number of the GOOD button. 
         [0076]    The member can also request a download of a browsed artwork (step SB 8 ). If a download request is made by a member, the server  11  permits the download if necessary (step SC 8 ) and the member can download a browsed artwork only if the download is permitted (step SB 9 ). The downloaded artwork is stored in the downloaded artwork memory  110  of the member area  100 . 
         [0077]    If a download request is made, the server  11  also adds up a point to the artwork (step SC 9 ). 
         [0078]    On the other hand, other users other than members, that is, any user can browse artwork stored in the artwork area  202  of the common area  200  in a state of the display at a glance by appropriately accessing the server  11  (step SA 1 ). Further, any user can also browse any artwork displayed at a glance in the actual size by making a request of browsing (step SA 2 ). 
         [0079]    Then, if any user presses the GOOD button because the browsed artworks suits his (her) taste (step SA 3 ), the server  11  also adds up a point to the browsed artwork (step SC 7 ). 
         [0080]    Next, the technology of snapshot-to-painting conversion processing when the server  11  converts uploaded image data into a painting image will be described. 
         [0081]    The snapshot-to-painting conversion is an image processing technology to convert each pixel constituting an original image such as a photo to an artwork according to predetermined parameters (snapshot-to-painting conversion parameters). The artwork includes an oil painting, an impasto, a gothic oil painting, a fauvist oil painting, a watercolor, a gouache, a pastel, a color pencil, a pointillism, a silk screen, a drawing, and an airbrush. These tones are called a style of paintings. 
         [0082]    The technology of snapshot-to-painting conversion image processing converts an original image to an image looking like a painting basically by automatically adjusting/combining parameters of various kinds of effect processing known as photo retouch software. 
         [0083]    Effect processing includes, for example, texture processing that provides a special texture by mapping the texture to an image and resolution processing that increases the texture and resolution by dividing an image into a contour portion, a texture portion such as a fine pattern, and a flat portion and performing appropriate processing on each portion. The effect processing also includes HSV processing that adjusts the color by dividing the color into three elements of the hue, saturation, and value, RGB processing that adjusts the degree of each color of R(red), G(green), and B(blue), and RGB substitution processing that makes a substitution in the direction of R to G, G to B, and B to R. The effect processing also includes an edge extraction processing that applies a filter called a 
         [0084]    Laplacian filter and an intermediate density extraction processing that applies a filter called a median filter. The effect processing also includes a density extraction processing that performs processing when a histogram in RGB of adjacent pixels is extracted to extract minimum/intermediate/maximum densities, an equalize processing that corrects the contrast or enlarges an image&#39;s histogram by setting the darkest portion of an image as black, the brightest portion as white, and appropriately distributing a histogram therebetween, a gamma correction processing that adjusts an intermediate brightness while maintaining a bright portion and a dark portion, and a shadow processing that brightens a dark portion of an image or darkens a bright portion thereof. The effect processing also includes a solarization processing that when the RGB value of each pixel is brighter than a threshold, inverts the RGB value thereof and a noise addition processing that adjusts the quantity and color of noise by randomly drawing dots to cause noise. 
         [0085]    The effect processing also includes an effect processing called HDR (High Dynamic Range) in which a photo with a wide dynamic range that cannot be expressed by an ordinary photo is compressed into a narrow dynamic range width through tone mapping to correct whiteout due to overexposure and black crushing due to underexposure so that power of expression is increased. By applying this effect processing, an image realizing a new photo expression that brings a photo closer to memories or impressions a person&#39;s brain has received and adds an artistic expression can be obtained. 
         [0086]    That is, the snapshot-to-painting conversion processing is in principle a kind of effect processing and a snapshot-to-painting conversion algorithm creates various kinds of painting tone by appropriately combining effect processing and parameters and is programmed as the snapshot-to-painting conversion processing. 
         [0087]    In the conversion algorithm, a parameter group P, which is a set of the parameters to convert pixels of an original image, is prepared in advance. If there are 12 kinds of painting tones, parameter groups are represented as P 1  to P 12 . How to determine parameters also changes the tone of a converted image. If the parameter group for the conversion into an oil painting tone is P 1  and there are m parameters in P 1  needed for effect processing to convert an image so as to look like a painting tone image, the parameter group P 1  contains a plurality of parameters P 1   1  to P 1   m . 
         [0088]    Generally, pixels are expressed by gradation of a plurality of bits of each of R, G and B. Parameters are elements for carrying out an operation for bit data. For example, coefficients “2”, “0.9” and “0.5” which are used when an operation “R×2, G×0.9, B×0.5” is performed to emphasize a red component and slightly suppress a green component and a blue component are parameters. 
         [0089]    As another example, emphasis degrees which are used in the case where operation elements are programmed in advance and an operation “R×1.1” is performed when the emphasis degree of red is 1, an operation “R×1.2” is performed when the emphasis degree of red is 2, and an operation “R×1.3” is performed when the emphasis degree of red is 3 are also parameters. 
         [0090]    In addition, there are cases where a predetermined operation is performed between a target pixel and adjacent pixels. For example, as illustrated in  FIG. 10A , when a target pixel A 5  (RGB) is located in the center and pixels A 1  (RGB), A 2  (RGB), A 3  (RGB), A 4  (RGB), A 5  (RGB), A 6  (RGB), A 7  (RGB), A 8  (RGB), and A 9  (RGB) are arranged above, under, on the left, and on the right of the target pixel A 5 , an operation “A5 (R)=A1(R)×q1+A2(R)×q2+A3(R)×q3+A4(R)×q4+A5(R)×q5+A6(R)×q6+A7(R)×q7+A8(R)×q8+A9(R)×q9” is performed for A 5 (R), and the same operation is performed for G and B. The element “q” in the operation is a parameter, and different effect processing can be performed by changing the value (coefficient). 
         [0091]    In addition, there is effect processing to process the image to change the touch. 
         [0092]    Specifically, pixels which closely correlate with each other based on colors are collected from pixels which form the image data, and grouped. Then, for pixels of each of the groups, the colors of pixels which belong to the same group are replaced by a representative color of the group. The group of pixels, colors of which are replaced by the representative color, forms each touch. According to the image processing described above, a touch which is formed can be changed, by changing correlation between pixels collected as a group and changing the shape (length (distance), flatness) of the group formed of pixels of the same color (representative color). As a result, it is possible to change the tone of the image indicated by the image data to various pictorial tones. 
         [0093]    In addition, an optimum combination of parameters such as correlation used for each processing, and the length and flatness which indicate the shape of the group is set for each tone. 
         [0094]    For example, when the shape of the group formed of pixels which closely correlate with the target pixel A 5  is the shape illustrated in  FIG. 11A  or  FIG. 11B , the shape illustrated in  FIG. 11A  has larger flatness and shorter length (distance) than those of the shape illustrated in  FIG. 11B . 
         [0095]    Changing each of a plurality of image data items into different touches can be realized by controlling the shape of each group obtained by collecting pixels forming a touch, for example, controlling the flatness of the group, when the tone is changed. The touch is thickened when the flatness of the group formed of pixels of the same color which indicates the touch is increased, and consequently the touch of the image is displayed in a coarse manner. A small touch can be formed by decreasing the flatness of the group formed of pixels of the same color, and consequently the touch of the image is displayed in a fine manner. 
         [0096]    The snapshot-to-painting conversion algorithm detailed above is stored in the snapshot-to-painting conversion processor  302  in the control area  300  of the server  11 . The parameters are also stored in the parameter table  304  of the control area  300 . 
         [0097]      FIG. 9  is a flowchart illustrating the snapshot-to-painting conversion processing performed by the snapshot-to-painting conversion processor  302 . In the server  11 , the snapshot-to-painting conversion processor  302  performs preprocessing, as illustrated in 
         [0098]      FIG. 6  (Step SC 101 ). This is processing which is performed in common, regardless of the type of the tone. 
         [0099]    The effect processing described above is performed for each pixel, and thus it is necessary that the image data is in the bit map form. Therefore, the snapshot-to-painting conversion processor  302  converts the image data, which is generally expressed in JPEG, into the bit map form. 
         [0100]    In addition, since the image data items which are uploaded from the terminals  1 - 1 ,  1 - 2 ,  1 - 3  . . . have various sizes, the snapshot-to-painting conversion processor  302  resizes the image data items to the number of pixels of the display area, for example, 800×600 pixels. Images of a larger size are reduced, and images of a smaller size are enlarged. This is because fixed parameters can be used for images of a fixed size, and thus the processing can be performed efficiently. As a matter of course, snapshot-to-painting conversion is performed for the image having the size of the uploaded image data, in snapshot-to-painting conversion described later. 
         [0101]    Next, the snapshot-to-painting conversion processor  302  checks by face detection processing whether the image to be converted includes a face or not (Step SC 102 ). This is performed to subject a face region of the image to snapshot-to-painting conversion which is different from snapshot-to-painting conversion for other parts, since the face region which is subjected to extreme conversion becomes unnatural. More specifically, the face region should be subjected to snapshot-to-painting conversion processing with conversion intensity lower than that for the other parts, or more detailed snapshot-to-painting conversion processing than that for the other parts. Basically, this is checked to subject the image to be converted to snapshot-to-painting conversion processing such that the face region in the converted image is closer to that in the original image to be converted than the other parts are. 
         [0102]    The term “detailed” means that the group of pixels which are subjected to effect processing is reduced. For example, in the case of smoothing or airbrushing, a group is formed between pixels adjacent to the target pixel A (x, y), an average of the pixels is obtained, values of the pixels in the group are replaced by the average value, and thereby smoothing or airbrushing is performed. For example, when pixels A 1 , A 2 , A 3 , A 4 , (A 5 ), A 6 , A 7 , A 8 , and A 9  are adjacent to the target pixel A 5  serving as the center, suppose that grouping four pixels of A 2 , A 4 , A 6 , and A 8  located above, under, on the left and on the right of the pixel A 5  (see  FIG. 10B ) is more detailed than grouping eight pixels of A 1  to A 9  around the pixel A 5  (see  FIG. 10C ) and grouping  24  pixels also including pixels around the eight pixels (see  FIG. 10D ) (the opposite of “detailed” is “coarse”). 
         [0103]    According to the type of the tone, a group of an irregular shape may be formed as illustrated in  FIG. 10E . Also in this case, suppose that subjecting a smaller group to snapshot-to-painting conversion for each smaller number of pixels is more detailed than subjecting a group of a large number of pixels together to snapshot-to-painting conversion. 
         [0104]    In the same manner, also with respect to the touch, suppose that processing groups, each of which is formed of a small number of pixels as illustrated in  FIG. 11A , many times is more detailed than processing groups, each of which is formed of a large number of pixels as illustrated in  FIG. 11B , few times. In the face detection processing, as will be described later by using the flow chart in  FIG. 12 , importance changes even in an image between a face region and the background or between a center portion and a peripheral portion and thus, the snapshot-to-painting conversion processor  302  creates a face region map indicating a face region of a person in the object image and stores it into the face region map  306  in the control area  200 . 
         [0105]    Subsequently, the snapshot-to-painting conversion processor  302  causes the user to select the desired painting tone from the oil painting, impasto, gothic oil painting, fauvist oil painting, watercolor, gouache, pastel, color pencil, pointillism, silk screen, drawing, and airbrush. (step SC 103 ). 
         [0106]    If the painting tone is selected, the snapshot-to-painting conversion processor  302  proceeds to the flow of each painting tone conversion algorithm. If, for example, the oil painting tone is selected, the snapshot-to-painting conversion processor  302  proceeds to step SC 104  and if the watercolor painting tone is selected, the snapshot-to-painting conversion processor  302  proceeds to step SC 105 . Otherwise, the snapshot-to-painting conversion processor  302  proceeds to the flow of other painting tone conversion algorithms (step SC 106 ). Incidentally, when executing each algorithm, the snapshot-to-painting conversion processor  302  references the parameter table  304  and the importance map  306  of the control area  300  (steps SC 107 , SC 108 , SC 109 , SC 110 ). 
         [0107]    In the processing in steps SC 104 , SC 105 , SC 106 , the snapshot-to-painting conversion processor  302  makes a snapshot-to-painting conversion intended for image data of the display screen size. If a decision is instructed from the terminal  1 - 1  of the user (step SC 112 : YES), proceeds to the snapshot-to-painting conversion of the original image (step SC 113 ) and, if redoing in another painting tone is instructed (step SC 112 : NO), returns to the processing in step SC 103 . 
         [0108]    For the snapshot-to-painting conversion of the original image in step SC 113 , the snapshot-to-painting conversion processor  302  performs painting tone conversion processing on the original image based on the painting tone conversion algorithm determined in step SC 112  while referencing the parameter table  304  and the importance map  306  (steps SC 114 , SC 115 ). If the image sizes are different, appropriate parameters are different even if the painting tone is the same and thus, the parameter table used in step SC 115  is different from parameters used in step SC 107  or SC 108 . 
         [0109]    Then, the snapshot-to-painting conversion processor  302  performs post-processing to convert the converted original image back to the JPEG format (step SC 116 ). 
         [0110]    Next, the face detection processing in step SC 102  by the snapshot-to-painting conversion processor  302  described above and a procedure for creating a face region map will be described with reference to  FIGS. 12 to 14A  and  14 B. 
         [0111]    In the face detection processing, as shown in  FIG. 12 , the snapshot-to-painting conversion processor  302  first analyzes the target image data to determine whether there is any face therein (step SC 151 ). Any known face detection technology can be used and thus, a detailed description thereof is omitted. 
         [0112]    In the face detection processing, even if a face is detected, it is difficult to accurately extract the contour thereof and thus, the snapshot-to-painting conversion processor  302  sets an elliptic or rectangular region containing a face region to the image data (step SC 152 ). 
         [0113]      FIG. 13  is a diagram illustrating a region containing a face region. A rectangular region “sq” contains a face Fl and an elliptic region “el” contains the face Fl. Thus, the regions “sq” and “el” correspond to the detected face regions. The rectangular region “sq” contains the detected face and the elliptic region “el” contains the rectangular region “sq”. 
         [0114]    Then, the snapshot-to-painting conversion processor  302  creates a face region map (step SC 153 ).  FIGS. 14A and 14B  are diagrams illustrating the face region map. In the processing in step SC 153 , if the snapshot-to-painting conversion processor  302  detects faces F 1 , F 2 , F 3  from image data as shown in  FIG. 14A , the snapshot-to-painting conversion processor  302  sets face regions sq 1 , sq 2 , sq 3  as shown in  FIG. 14B  to the image data. That is, the snapshot-to-painting conversion processor  302  stores data indicating the face regions sq 1 , sq 2 , sq 3  into the face region map  306  in the control area  300 . 
         [0115]    Then, when performing snapshot-to-painting conversion processing on each pixel of image data at steps SC 104 , SC 105 , SC 106 , or SC 113 , the snapshot-to-painting conversion processor  302  sets low conversion intensity for the face regions, and sets high conversion intensity for the background region excluding the face regions to perform snapshot-to-painting conversion, or perform more detailed snapshot-to-painting conversion for the face regions than that for the background region, based on the face region map illustrated in  FIG. 14B . 
         [0116]    Since many effect processing, which vary according to the type of the tone, are performed in the snapshot-to-painting conversion (see  FIGS. 15A to 15D ), low or detailed conversion intensity is set for each conversion processing. Performing the snapshot-to-painting conversion together results in performing the snapshot-to-painting conversion by setting low conversion intensity for the face regions, and setting high conversion intensity for the background region excluding the face regions, and performing more detailed snapshot-to-painting conversion for the face regions than that for the background region. Therefore, the processing of setting the conversion intensity exists together with the processing of setting the detail degree. 
         [0117]    As a result, in the painting image after snapshot-to-painting conversion, the face regions have a little difference from the original image, and the background region has a large difference from the original image. 
         [0118]    Therefore, even when a human face exists in the original image, the atmosphere of the face does not deteriorate, and natural snapshot-to-painting conversion can be performed. It is an example as a matter of course, and the face regions sq 1 , sq 2 , and sq 3  may not be subjected to snapshot-to-painting conversion to prevent deterioration of the atmosphere of the face. 
         [0119]    The conversion intensity in the snapshot-to-painting conversion will be explained in detail hereinafter. The magnitude of the conversion intensity basically means the size of parameters explained above. Specifically, the magnitude of the conversion intensity means the size of parameters P 1  to Pm which are necessary for the effect processing mentioned as an example above, the elements (coefficients) with which an operation is performed for bit data of each of R, G and B of each pixel, the color emphasis degree, a value (coefficient) q which is used when a predetermined operation is performed between the target pixel and adjacent pixels, and the shape (such as length and flatness) of the pixel group used when a touch is expressed. Specifically, the difference of a part of the painting image from the original image increases as the parameters increase. 
         [0120]    Generally, conversion of an image means mapping the original image onto another image. When mapping is performed, a predetermined conversion is performed. In the conversion, a difference between the original image and the image obtained by conversion is small when a conversion coefficient (parameter) is small. When the conversion coefficient is the minimum, there is no difference between the original image and the image obtained by conversion, and the same image is obtained. When the conversion coefficient is large, a difference between the original image and the image obtained by conversion becomes conspicuous. 
         [0121]    Conversion of an image can be indicated by the following expression, when a pixel value of the original image is A, a pixel value of an image obtained by conversion is B, and the conversion algorithm is f: 
         [0000]        B=f ( A ) 
         [0122]    The reference symbol f represents, for example, a plurality of types of effect processing, such as texture processing, HSV processing, Laplacian filtering, or median filtering. In addition, the reference symbol f represents processing of converting an image into, for example, an oil-painting tone image, or a pastel tone image. 
         [0123]      FIG. 15A  is a diagram which schematically illustrates the contents of processing of snapshot-to-painting conversion as generalization. As illustrated in  FIG. 15A , the conversion algorithm actually includes individual algorithms of a plurality of types of effect processing  1  to N. 
         [0124]      FIG. 15B  is a schematic diagram which corresponds to  FIG. 15A , and illustrates processing performed when a target tone is a certain tone. As illustrated in  FIG. 15B , the conversion algorithm includes algorithms of specific types of effect processing  1 ,  7 ,  9 , . . . and M which correspond to the target tone. 
         [0125]    On the other hand, conversion of an image, which includes elements of the conversion intensity can be indicated by the following expression: 
         [0000]        B=f ( A, I ) 
         [0126]    Reference symbol I represents intensity. 
         [0127]    For example, photo-retouch software which is generally used in personal computers can perform various image processing, intensity of which can be controlled. The intensity which is controlled in the image processing corresponds to the value of I. 
         [0128]    The conversion algorithm f includes not only processing of maintaining the position of a pixel (x, y), but also processing of moving the position of a pixel or a group of pixels. For example, a distorted image can be obtained by moving a pixel of (x 1 , y 1 ) to (x 3 , y 4 ), and moving pixels around the pixel together. In this case, the conversion intensity increases as the moving distance increases. In addition, the conversion algorithm f also includes various airbrushing processing. For example, in the airbrushing processing of setting an average value of surrounding pixels for a target pixel, the conversion intensity increases as the number of surrounding pixels increases. 
         [0129]    In the snapshot-to-painting conversion at the Steps SC 104 , SC 105 , SC 106 , and SC 113  described above, different conversion intensities are set for the face regions shown in the face region map and the background region excluding the face region. Specifically, in snapshot-to-painting conversion, a target pixel to be processed is subjected to processing, to which a conversion intensity I that is set for the region including the target pixel is applied. Thereby, the original image is converted into a painting image, in which the face region has a little difference from that of the original image, and the background region has a large difference from that of the original image. 
         [0130]      FIG. 15C  is a diagram which corresponds to  FIG. 15B  and schematically illustrates the contents of processing of snapshot-to-painting conversion, to which the conversion intensity I that is set for the region including the target pixel is applied. As illustrated in  FIG. 15C , in the snapshot-to-painting conversion, processing which reflects the conversion intensity I corresponding to the region shown in the face region map is performed for the target pixel, in each of a plurality of types of effect processing  1 ,  7 ,  9 , . . . and M. As a result, the original image is subjected to snapshot-to-painting conversion in which the conversion intensity for the face regions is different from the conversion intensity for the background region. 
         [0131]    In short, in snapshot-to-painting conversion at steps SC 104 , SC 105 , SC 106 , and SC 113  described above, the processing of the above expression “B=f(A, I)” is performed for all the pixels of the image data, and the value of I is changed according to whether the pixel belongs to the face region or the background region. Some types of the target tone include effect processing on which the conversion intensity I is not reflected. 
         [0132]    The above snapshot-to-painting conversion can be processing in which the conversion intensity for each region shown in the face region map  306  is reflected on an α value (transmission information of each pixel, which is different from color expression data R, G, and B) which forms an a map which is publicly known (see Jpn. Pat. Appin. KOKAI Publication No. 2002-325171 and Jpn. Pat. Appin. KOKAI Publication No. 2009-237927), and a blending is performed for a converted image temporarily obtained by snapshot-to-painting conversion with a conversion algorithm according to the tone and the original image. 
         [0133]      FIG. 15D  is a diagram which corresponds to  FIG. 15C  and schematically illustrates the contents of processing of snapshot-to-painting conversion by a blending. 
         [0134]    Snapshot-to-painting conversion by a blending is indicated by the following expression, when the original pixel value is A, the converted pixel value is B, and each pixel value of the α map is α (0.0 to 1.0): 
         [0000]        B=α×A +(1.0−α)× f ( A )
 
         [0135]    Therefore, for example, when a converted image is superposed on and blended with the original image, a degree of expressing the original image through the converted image can be increased in the face regions (sq 1 , sq 2 , and sq 3  in  FIG. 14B ), by increasing the a value of pixels in the face regions having low conversion intensity, and decreasing the a value of pixels in the background region having high conversion intensity. Specifically, it is possible to reduce a difference of the face regions from the original image and increase a difference of the background region from the original image, in the painting image which is obtained in the end. 
         [0136]      FIG. 16  illustrates a state where a region (boundary region) of an outline part of the face region sq is further divided. For example, when conversion intensity is varied between the inside and the outside of the outline of the face region “sq”, a difference in level in which a difference in atmosphere is evident may be generated in the painting image. Therefore, an oval region “el” as illustrated in  FIG. 16  may be set outside the face region “sq”, an oval region “el 5 ” which encloses the region el and a size larger than the region “el” may be set outside the region “el”, and the conversion intensities of the regions “sq”, “el”, and “el 5 ” may have the relation “sq&gt;el&gt;el 5 ”. The same is applicable to the case where more detailed snapshot-to-painting conversion is performed for the face region “sq” than that for the background region. Thereby, the outline part of the face can be subjected to snapshot-to-painting conversion in stages to have natural impression. 
         [0137]    In the service site  10  of the present embodiment, download is performed as illustrated in  FIG. 17 . Member registration is required for performing download in the site. 
         [0138]      FIG. 17  is a flow chart showing processing concerning a download of an artwork on the server  11 . The processing in  FIG. 17  is performed by the CPU  20  of the server  11 , the evaluation controller  310 , and the membership management unit  312 . 
         [0139]    If the artwork desired by a member to download is specified on the server  11  (step SC 201 ), the membership management unit  312  determines whether the user is a pay member (here, an ordinary pay member or a premium member) or a free member (step SC 202 ). If the user is a pay member, immediately proceeds to step SC 207  described later. 
         [0140]    On the other hand, the user is a free member, the membership management unit  312  reads the point corresponding to the evaluation of the artwork from the attribute information  206  of the artwork (step SC 203 ) and also reads the point held by the member who is about to download from the attribute information thereof (step SC 204 ). 
         [0141]    Next, the membership management unit  312  calculates a payment point from the balance of the point (corresponding to the evaluation) of the artwork and the point held by the member (step SC 205 ). If the payment point is sufficient, the membership management unit  312  proceeds to step SC 207 . But if the payment point is insufficient, the artwork cannot be downloaded and the membership management unit  312  returns to step SC 201  to cause the user to select another artwork. 
         [0142]    Then, on the server  11 , the CPU  20  reads the artwork specified by the user from the artwork memory  108  of another user who is the creator of the artwork (step SC 207 ) and the evaluation controller  310  adds up a point to each of the creator of the artwork and the artwork (step SC 208 ). That is, things are arranged for members (free members, pay members, and premium members) so that the evaluation of artworks rises with an increasing number of downloads of members&#39; artworks and also a point is added to the point area in the attribute information of the user ID  206  of the member who is the creator, which increases the points held by the member. 
         [0143]    Then, on the server  11 , the CPU  20  performs download processing that stores the artwork read in step SC 207  in the downloaded artwork memory  110  of the user who has requested the download thereof (step SC 209 ). 
         [0144]    Since the image service cite  10  has a social network service function, the user can add comments in an artwork of other users, reply to the comments, form a group with users having similar preference, or form an association of a particular artiest. These functions are well-known in the current SNS so that detailed description is omitted. The membership management unit  312  controls the SNS function as well as the membership management. 
         [0145]    According to the present embodiment described above, it is possible to ideally perform snapshot-to-painting conversion for aim image including a person. Different conversion intensities are used for the face region and parts other than the face, thereby unnaturalness of the whole painting image is removed, and snapshot-to-painting conversion which produces natural appearance of faces can be realized. 
         [0146]    While the description above refers to particular embodiments of the present invention, it will be understood that many modifications may be made without departing from the spirit thereof. The accompanying claims are intended to cover such modifications as would fall within the true scope and spirit of the present invention. The presently disclosed embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims, rather than the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. For example, the present invention can be practiced as a computer readable recording medium in which a program for allowing the computer to function as predetermined means, allowing the computer to realize a predetermined function, or allowing the computer to conduct predetermined means. For example, a region which corresponds to a face may be cut out of the image data  208 , the region corresponding to the face and the other region may be subjected to snapshot-to-painting conversion separately from each other, and thereafter combined with each other.