Abstract:
Disclosed herein is a method and apparatus for editing an image using an object contour extracted from an input image. The method of editing an image using a contour-extracting algorithm includes: inputting image data; extracting an object contour from the input image data; optimizing the extracted contour using the characteristics of the input image data; editing the input image data using the optimized contour; and outputting the edited image data.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS  
       [0001]     This application claims the benefit of Korean Patent Application No. 10-2005-0131986, filed on Dec. 28, 2005, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference.  
       BACKGROUND OF THE INVENTION  
       [0002]     1. Field of the Invention  
         [0003]     The present invention relates to a method and apparatus for editing an image using a contour-extracting algorithm, and more particularly to a method and apparatus for editing an image using a contour extracted from an input image.  
         [0004]     2. Description of the Related Art  
         [0005]     A conventional object contour-extracting method using an energy-based algorithm is described in U.S. Pat. No. 6,912,310 in which an object is extracted from a first image frame and then object template matching is performed for a subsequent image frame. However, such an object contour-extracting method has a problem in that in the case of application to a video with a complex background, an edge portion of an object contour as well as a background within the video is increased in density, which makes it difficult to substantially and precisely identify the object contour.  
         [0006]     Also, a conventional object contour-extracting method based on color and motion region segmentation is described in U.S. Pat. No. 6,785,329 in which a video is segmented in a Blob format using color information and the object contour is extracted through the segmentation and combination of Blobs. However, such an object contour-extracting method encounters a problem in that in the case of application to a video with a complex background, the video is segmented into a huge number of Blobs, which makes it difficult to substantially and precisely identify the contour of the object.  
         [0007]     Also, in the case of a conventional contour model-based object contour-extracting method, the contour model is formed using a training sample and contour searching is performed to maintain the form of the contour model. But such a contour model-based object contour-extracting method also has a shortcoming in that it depends on learning a data characteristic since control points are detected based only on the contour model, such that if there is a slight difference between learned contour models, it is difficult to identify an appropriate object contour.  
         [0008]     As such, the conventional object contour-extracting methods make it difficult to substantially and precisely identify an object contour.  
         [0009]     Therefore, there is an urgent need for a solution that substantially and precisely detects a contour of an object and edits an image using the detected contour.  
       SUMMARY OF THE INVENTION  
       [0010]     Accordingly, the present invention has been made in view of the aforementioned problems occurring in the prior art, and it is an aspect of the present invention to provide a method and apparatus for editing an image using an object contour to extract, from a complex background image, a body in a foreground.  
         [0011]     Another aspect of the present invention is to provide an image-editing method and apparatus, in which an object contour extracted from an image data is optimized to be synthesized with any other background scene.  
         [0012]     Still another aspect of the present invention is to provide an image-editing method and apparatus, in which an object contour extracted from an image data is optimized, a clothing region and a facial region of the image object, i.e. a person, is segmented using skin color detection, and the shape of the segmented clothing region and the brightness of the segmented facial region are adjusted.  
         [0013]     Yet another aspect of the present invention is to provide an image-editing method and apparatus, in which an object contour extracted from image data is optimized, and the brightness of the background region is then adjusted.  
         [0014]     According to one aspect of the present invention, there is provided a method of editing an image using an object contour-extracting algorithm, the method including: inputting image data; extracting an object contour from the input image data; optimizing the extracted contour using the characteristics of the input image data; editing the input image data using the optimized extracted contour; and outputting the edited image data.  
         [0015]     According to another aspect of the present invention, there is also provided an apparatus for editing an image using an object contour-extracting algorithm, the apparatus including: an image input section for inputting image data; an object contour-extracting section for extracting an object contour from the input image data applied to the object contour-extracting section from the image input section; an object contour-optimizing section for optimizing the extracted contour applied to the object contour-optimizing section from the object contour-extracting section using the characteristics of the input image data; an image-editing section for editing the image data using the optimized extracted object contour applied to the image-editing section from the object contour-optimizing section; and an image output section for outputting the edited image data applied thereto from the image-editing section.  
         [0016]     Additional aspects and/or advantages of the invention will be set forth in part in the description which follows and, in part, will be apparent from the description, or may be learned by practice of the invention. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0017]     The above and/or other aspects and advantages of the present invention will become apparent and more readily appreciated from the following detailed description, taken in conjunction with the accompanying drawings of which:  
         [0018]      FIG. 1  is a block diagram illustrating the inner construction of an apparatus for editing an image using an object contour-extracting algorithm according to one embodiment of the present invention;  
         [0019]      FIG. 2  is a flowchart illustrating the process of editing an image using an object contour-extracting algorithm according to one embodiment of the present invention;  
         [0020]      FIG. 3  is a flowchart illustrating the process of extracting an initial object contour in the image-editing method according to an embodiment of the present invention;  
         [0021]      FIG. 4  is an example of image data used in the process of initially extracting an object contour in the image-editing method according to an embodiment of the present invention;  
         [0022]      FIG. 5  is a flowchart illustrating the process of optimizing the extracted object contour in the image-editing method according to an embodiment of the present invention;  
         [0023]      FIG. 6  is an example of detection of control points in the image-editing method according to an embodiment of the present invention;  
         [0024]      FIG. 7  is a diagram illustrating an example for updating a contour model in the image-editing method according to an embodiment of the present invention;  
         [0025]      FIG. 8  is a flowchart illustrating a user correction process in the image-editing method according to an embodiment of the present invention;  
         [0026]      FIG. 9  is a flowchart illustrating a process for editing the image data using the optimized object contour in the image-editing method according to an embodiment of the present invention;  
         [0027]      FIG. 10  is a pictorial diagram illustrating an example of an image editing process for inserting an image object, i.e. a person, into a background image in the image-editing method according to an embodiment of the present invention;  
         [0028]      FIG. 11  is a flowchart illustrating a process for inserting an image object, i.e. a person, into the background image of  FIG. 9  in the image-editing method according to an embodiment of the present invention; and  
         [0029]      FIG. 12  is a flowchart illustrating a process for editing images for clothing and facial regions of a person in the image-editing method according to an embodiment of the present invention. 
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0030]     Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout. The embodiments are described below in order to explain the present invention by referring to the figures.  
         [0031]      FIG. 1  is a block diagram illustrating the inner construction of an apparatus for editing an image using an object contour-extracting algorithm according to one embodiment of the present invention.  
         [0032]     Referring to  FIG. 1 , an image-editing apparatus  100  is shown that includes an image input section  110 , an object contour-extracting section  120 , an object contour-optimizing section  130 , an image-editing section  140 , and an image output section  150 .  
         [0033]     The image input section  110  is inputted with image data including data of a person that is to be edited.  
         [0034]     The object contour-extracting section  120  extracts an object contour from the input image data applied thereto from the image input section  110 . That is, the contour-extracting section  120  can detect at least one of a face, eyes, and a skin color of an image object, i.e. a person, from the input image data, or extract a position of the person through an entry of a user and extract an initial object contour from the data of the person, which is contained in the image data using a specific contour model.  
         [0035]     The object contour-optimizing section  130  optimizes the extracted object contour applied thereto from the object contour-extracting section  120  using the characteristics of the input image data. That is, the object contour-optimizing section  130  can optimize the extracted initial contour using characteristics of energy or an edge of the input image data.  
         [0036]     The image-editing section  140  edits the input image data using the optimized contour applied thereto from the contour-optimizing section  130 .  
         [0037]     The image-editing section  140  can edit the image data using the optimized contour to segment a clothing region and a facial region of an image object, i.e. a person, using skin color detection, and adjust the shape of the segmented clothing region and the brightness of the segmented facial region. The image-editing section  140  can also edit the image data to adjust the brightness of a background region for the image data.  
         [0038]     The image output section  150  outputs the edited image data applied thereto from the image-editing section  140 .  
         [0039]     As such, the image-editing apparatus according to the present invention extracts an object contour from the input image data, such as a contour of a person, and optimizes the extracted contour to more precisely detect the contour of the object, for example, the person.  
         [0040]     Accordingly, the image-editing apparatus according to the present invention can edit the image in various fashions such as synthesizing an image object, i.e. a person, with any other background image, deforming the clothing shape or the face of the person, adjusting the brightness of the background screen, etc., using the precisely detected object contour.  
         [0041]      FIG. 2  is a flowchart illustrating a process of editing an image using a contour-extracting algorithm according to one embodiment of the present invention.  
         [0042]     Referring to  FIG. 2 , in operation  210 , the image-editing apparatus according to the present invention is input with image data including data of a person that is to be edited.  
         [0043]     In operation  220 , the image-editing apparatus  100  extracts an object contour from the input image data. The process for extracting an initial contour in operation  220  will be described hereinafter in more detail with reference to  FIG. 3 .  
         [0044]      FIG. 3  is a flowchart illustrating the process for extracting an initial object contour in the image-editing method according to an embodiment of the present invention.  
         [0045]     Referring to  FIG. 3 , in operation  310 , the image-editing apparatus  100  extracts a position of an image object, i.e. a person, from input image data  410  as shown in  FIG. 4 . For example, in operation  310 , the image-editing apparatus  100  detects at least one of a face, eyes, and a skin color of the person from the input image data, or extracts the position of the person through entry by a user.  
         [0046]     In operation  320 , the image-editing apparatus  100  extracts initial contour data  430  from the input image data  410  using a specific object contour model  420  as shown in  FIG. 4 .  
         [0047]     In operation  320 , the image-editing apparatus  100  can extract the size of the person based on, for example, the distance between both eyes of the detected person, and then map the specific contour model  420  to the input image data  410  to extract the initial object contour data  430 .  
         [0048]     The initial contour data  430  allows the contour for the input image data  410  to be represented as control points for main pixels.  
         [0049]     In operation  320 , the image-editing apparatus  100  extracts the size of the person based on, in this example, the distance between both eyes of the person, and subjects the extracted size of the person to a model scaling to represent the object contour as control points.  
         [0050]     In operation  320 , the image-editing apparatus  100  can represent the contour model by eigenvectors generated using training images labeled manually by a principle component analysis (PCA).  
         [0051]     In operation  330 , the image-editing apparatus  100  extracts gradient information included in a gradient vector flow (GVF) image data  440  shown in  FIG. 4  from the input image data.  
         [0052]     Also, in operation  330 , the image-editing apparatus  100  can extract the gradient information from the input image data  410  using a gradient vector flow (GVF). A gradient direction of the image in the GVF denotes a direction in which an edge density of a pixel is high. That is, according to the GVF image data  440  as shown in  FIG. 4 , a zero crossing in which the direction of the gradient vector alters occurs in the pixel whose edge density is high.  
         [0053]     Subsequently, in operation  340 , the image-editing apparatus  100  modifies the extracted initial contour data to conform to the extracted gradient information from the input image data.  
         [0054]     In operation  340 , the image-editing apparatus  100  can move the control points of the initial contour to a neighboring pixel whose edge density is high.  
         [0055]     Namely, in operation  340 , the image-editing apparatus  100  can provide the modified object contour image data  450  as shown in  FIG. 4  by moving the control points of the initial object contour to a point where the direction of the gradient vector alters.  
         [0056]     As such, the image-editing method according to an embodiment of the present invention can extract the initial object contour in a form as close as possible to the form of the person so as to increase precision and efficiency in detection of the contour.  
         [0057]     In operation  230 , the image-editing apparatus  100  optimizes the extracted object contour using characteristics of the input image data. The process for optimizing the extracted contour in operation  230  will be described hereinafter in more detail with reference to  FIG. 5 .  
         [0058]      FIG. 5  is a flowchart illustrating the process of optimizing the extracted object contour in the image-editing method according to an embodiment of the present invention.  
         [0059]     Referring to  FIG. 5 , in operation  510 , the image-editing apparatus  100  retrieves the optimum object contour using the characteristics of the input image data and a specific learned contour model.  
         [0060]     That is, in operation  510 , the image-editing apparatus  100  can retrieve control points of the optimum object contour from current image data using the characteristics of the input image data and the contour model.  
         [0061]     In operation  510 , as shown in  FIG. 6 , the image-editing apparatus  100  can select a neighboring pixel in which a result value of an energy function (E) for a current control point  610  is a minimum, and determine the selected neighboring pixel as a next control point  620  which is a new control point. The energy function (E) is an objective function that specifies the condition for deciding the next control point corresponding to the object contour. The energy function (E) consists of E continuity , E smoothness , E Edge , E Shape , and E Color , as given by Equation 1 below: 
 
 E=α=E   continuity   +β×E   smoothness   +γ×E   Edge   κ×E   Shape   +λ×E   Color   [Equation 1]
 
 where α, β, γ, κ and λ denote the weighted values for respective terms of the energy function (E). 
 
         [0062]     E continuity  denotes a function representing whether or not a curve represented by the control point has continuity and can be represented as a first derivative value. The E continuity  can be expressed as given by Equation 2. 
 
 E   continuity   =∥p   i   −p   i−1 ∥ 2   [Equation 2]
 
 where p i  denotes information about the i th  pixel. E smoothness  denotes a function representing whether or not a curve represented by the control point is smoothly connected in a curvature form, has continuity and can be represented as a second derivative value. The E smoothness  can be expressed as given by Equation 3. 
 
 E   smoothness   ∥p   i−1 −2 ×p   i   +p   i+1 ∥ 2   [Equation 3]
 
         [0063]     E Edge  is a function representing whether or not a curve represented by the control point is similar to an edge of the input image data. E Edge  is a distance between the control point and a zero crossing point on the GVF image data and can be used as an edge density.  
         [0064]     E Shape  is a function representing whether or not a shape represented by the control point is similar to that of the object contour model. E Shape  is a comparison value between the control point and the contour model and can be expressed as given by Equation 4. 
 
 E   Shape   =∥C   i   −M   i ∥ 2 , 
 
C i =Control Points, M i =Model Control Points  [Equation 4]
 
         [0065]     E Color  is a function representing whether or not there is a difference in color in the surroundings of the control point and can be expressed as a reciprocal of a dispersion value of a color difference between the control point and the surrounding pixels. In this case, as the dispersion value of the color difference increases, the probability that the control point is within the boundary of the image object, i.e. the person, increases.  
         [0066]     In operation  520 , the image-editing apparatus  100  updates the contour model using the retrieved optimum object contour. In other words, in operation  520 , the image-editing apparatus  100  can modify the contour model by the sample to conform to the current object contour.  
         [0067]     In operation  520 , the image-editing apparatus  100  can assume a currently detected control point as an optimum control point and use the currently-detected control point to update the contour model.  
         [0068]     Also in operation  520 , the image-editing apparatus  100  can add a difference value between the currently-detected control point and the control point of the contour model to the control point of the contour model.  
         [0069]     In operation  520 , as shown in  FIG. 7 , the image-editing apparatus  100  allows a difference value (M t −C t ) between the control point (M t ) of the contour model and the currently-detected control point (C t ) to pass through a low-pass filter  710 , and then adds a value (M t −C t )′, in which a noise is eliminated, to the control point (M t ) of the contour model so that the control point (M t+1 ) of the updated contour model can be calculated as given by Equation 5. 
 
 M   t+1   =M   t +( M   t   −C   t )′[Equation 5]
 
         [0070]     In operation  530 , the image-editing apparatus  100  determines whether or not the detection of the contour from the input image data is completed. That is, in operation  530 , the image-editing apparatus  100  can restrict the detection completion test for the object contour to, for example, a number of times of detection, whether or not there is a convergence of the retrieval function of an optimum object contour, etc.  
         [0071]     If it is determined in operation  530  that the detection of the contour has not been completed, the program returns to operation  510 , and in this manner the image-editing apparatus  100  repeatedly performs the operation  510  until the detection of the object contour is completed.  
         [0072]     On the other hand, if it is determined in operation  530  that the detection of the contour has been completed, the process proceeds to operation  540 , where the image-editing apparatus  100  outputs a result of the automatically-detected contour.  
         [0073]     As such, the image-editing method according to the present invention precisely extracts the contour of an object image region to be synthesized so that the editing work using the extracted contour can be more naturally performed.  
         [0074]      FIG. 8  is a flowchart illustrating a user correction process in the image-editing method according to an embodiment of the present invention.  
         [0075]     Referring to  FIG. 8 , in operation  810 , the image-editing apparatus  100  receives a request for correction of the contour from a user to adjust the position of the control point for the automatically-detected contour. At this time, the user evaluates a result of the automatically-detected contour. If it is determined that the result of the automatically-detected contour is not satisfactory, the user can adjust the result of the automatically-detected contour through the request for correction of the contour.  
         [0076]     In operation  820 , the image-editing apparatus  100  adjusts the position of the control point for the automatically-detected contour in response to the received request for correction of the contour.  
         [0077]     In operation  830 , the image-editing apparatus  100  optimizes the object contour according to the energy function which has been altered due to the adjusted control point position.  
         [0078]     In operation  840 , the image-editing apparatus  100  determines whether or not the correction of the contour has been completed.  
         [0079]     If it is determined in operation  840  that the correction of the contour has not been completed, the program returns to the previous operation  820 , and in this manner the image-editing apparatus  100  repeatedly performs the operation  820  until the correction of the contour is completed.  
         [0080]     If, on the other hand, it is determined in operation  840  that the correction of the contour has been completed, the program proceeds to operation  850 , where the image-editing apparatus  100  outputs the final object contour in which the correction of the contour has been completed to provide the output contour to the user.  
         [0081]     As such, the image-editing method according to the present invention allows the user to adjust the result of the automatically-detected contour to provide a satisfactory contour result to the user.  
         [0082]     Referring back to  FIG. 2 , in operation  240 , the image-editing apparatus  100  edits the image data using the optimized object contour. The process for the image-editing apparatus  100  to edit the image data to insert the optimized personal contour into a background image in operation  240  will be described hereinafter in more detail with reference to  FIG. 9 .  
         [0083]      FIG. 9  is a flowchart illustrating a process for editing the image data using the optimized contour in the image-editing method according to an embodiment of the present invention.  
         [0084]     Referring to  FIG. 9 , in operation  910 , the image-editing apparatus  100  inserts the optimized contour into a predetermined background image. That is, in operation  910 , the image-editing apparatus  100  scales the optimized contour to conform to the background image at a position designated by a user or automatically designated by a system, and then inserts the scaled contour into the background image. As an example of editing image data, a position where an edge density of the background image is lowest may be designated as a position for the image object, i.e. the person, to be inserted in the system.  
         [0085]      FIG. 10  is a pictorial diagram illustrating an example of an imageediting process for inserting an image object, i.e. a person, into a background image in the image-editing method according to an embodiment of the present invention.  
         [0086]     Referring to  FIG. 10 , first image data  1010  is image data including data of a person to be edited, second image data  1020  is data of a person obtained by extracting an objectregion, i.e., a region including the image of the person, from the first image data  1010 . Third image data  1030  is image data including background data to be edited, and fourth image data  1040  is image data obtained by synthesizing the second image data  1020  as the extracted data of an object, i.e., a person, with the third image data  1030  as the background data.  
         [0087]     As such, the image-editing method according to the present invention may extract a contour from the input image data, and insert the extracted contour into background data, which a user wants to synthesize, in a suitable size.  
         [0088]     The process for the image-editing apparatus  100  to insert the image object, i.e. the person, into a background image in operation  910  will be described hereinafter in more detail with reference to  FIG. 11 .  
         [0089]      FIG. 11  is a flowchart illustrating a process for inserting an image object, i.e. a person, into the background image of  FIG. 9  in the image-editing method according to an embodiment of the present invention.  
         [0090]     Referring to  FIG. 11 , in operation  1110 , the image-editing apparatus  100  receives resolution information related to a background image, an object region including an image of a person, and the image of the person.  
         [0091]     In operation  1120 , the image-editing apparatus  100  calculates a scaling ratio between the image of the person and the background image. For example, in the case where a resolution of the image of the person is 320*240 and a resolution of the background image is 240*240, the width scaling ratio (W r ) between the image of the person and the background image is 0.75(240/320), and the height scaling ratio (H r ) between the image of the person and the background image is 1(240/240).  
         [0092]     In operation  1130 , the image-editing apparatus  100  generates a bounding box using the largest width and height in the object region. For example, in the case where the largest width is ‘40’ and the largest height is ‘80’ in the object region, the size of the bounding box is ‘40*80’.  
         [0093]     In operation  1140 , the image-editing apparatus  100  scales the object region to conform to the smaller one of the calculated width and height scaling ratios between the image of the person and the background image, and the ratio of the bounding box.  
         [0094]     The case where the width scaling ratio (W r ) is ‘0.75’, the height scaling ratio (H r ) is ‘1’, and the size of the bounding box is ‘40*80’ will be described hereinafter as an example.  
         [0095]     In operation  1140 , the image-editing apparatus  100  performs a sub-sampling for the width of the bounding box so that the size of the width scaling ratio and the width of the bounding box becomes ‘40*0.75=30’, and performs the sub-sampling for the height of the bounding box so that the ratio of the width and the height of the bounding box maintains a relationship of ‘40:80=1:2’.  
         [0096]     In operation  1150 , the image-editing apparatus  100  synthesizes the scaled object region with the background image. That is, in operation  1150 , the image-editing apparatus  100  replaces a pixel at a position defined within the background image with a pixel of the object region so that the scaled object region can be synthesized with the background image.  
         [0097]     In operation  920 , the image-editing apparatus  100  performs an image matting for the inserted contour. That is, in operation  920 , the image-editing apparatus  100  can employ Bayesian/Poisson matting method and the like to perform the image matting which adjusts a pixel value of the boundary (or edge) portion of the image object, i.e. the person, inserted into the background image so that the boundary portion of the person can be smoothly synthesized.  
         [0098]     In operation  240 , the image-editing apparatus  100  may edit the image for clothing/facial regions of the person using the optimized object contour. The process for the image-editing apparatus  100  to edit images for the clothing and facial regions of the person in operation  240  will be described hereinafter in more detail with reference to  FIG. 12 .  
         [0099]      FIG. 12  is a flowchart illustrating a process for editing images for the clothing and facial regions of a person in the image-editing method according to an embodiment of the present invention.  
         [0100]     Referring to  FIG. 12 , the image-editing apparatus  100  detects a skin color of the person from the optimized contour, and segments a clothing region and a facial region based on the detected skin color of the person.  
         [0101]     In operation  1220 , the image-editing apparatus  100  adjusts the shape of the segmented clothing region and the brightness of the segmented facial region.  
         [0102]     As such, in the image-editing method according to an embodiment of the present invention, the object contour is optimized from the input image data, a skin color of the person in the input image data is detected based on the optimized contour to segment the clothing region and the facial region, and the shape of the segmented clothing region and the brightness of the segmented facial region are adjusted so that a user can edit the input image data in the form of various images.  
         [0103]     In operation  240 , the image-editing apparatus  100  may edit the image data to adjust the brightness of the background region for the image data using the optimized contour.  
         [0104]     As such, in the image-editing method according to an embodiment of the present invention, the object contour is optimized from the input image data, the background region and the object region in the input image data are segmented based on the optimized contour, and the brightness of the segmented background region can be adjusted so that a user can adjust the background region.  
         [0105]     Therefore, the present invention can provide a more discriminating image-editing service in a variety of devices (for example, personal video recorders, home servers, smart mobile devices, etc.) which allow a user to store and view photographs and videos using an automated contour-extracting algorithm. In addition, since the contour can be extracted precisely, the present invention can be applied to a photo-browsing service.  
         [0106]     The image-editing apparatus according to the present invention may include a computer-readable medium including a program instruction for executing various operations realized by a computer. The computer-readable medium may include a program instruction, a data file, and a data structure, separately or cooperatively. The program instructions and the media may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind well known and available to those skilled in the art of computer software arts. Examples of the computer-readable media include magnetic media (e.g., hard disks, floppy disks, and magnetic tapes), optical media (e.g., CD-ROMs or DVD), magneto-optical media (e.g., floptical disks), and hardware devices (e.g., ROMs, RAMs, or flash memories, etc.) that are specially configured to store and perform program instructions. The media may also be transmission media such as optical or metallic lines, wave guides, etc. including a carrier wave transmitting signals specifying the program instructions, data structures, etc. Examples of the program instructions include both machine code, such as that produced by a compiler, and files containing high-level language codes that may be executed by the computer using an interpreter.  
         [0107]     According to the present invention, there is provided a method and apparatus for editing an image using an object contour to extract, from a complex background image, a body in a foreground.  
         [0108]     Also, according to an embodiment of the present invention, there is provided an image-editing method and apparatus, in which a contour extracted from image data is optimized to be synthesized with any other background scene.  
         [0109]     Further, according to an embodiment of the present invention, there is provided an image-editing method and apparatus, in which an object contour extracted from image data is optimized, a clothing region and a facial region of an image object, i.e. a person, is segmented using skin color detection, and the shape of the segmented clothing region and the brightness of the segmented facial region are adjusted.  
         [0110]     Further still, according to an embodiment of the present invention, there is provided an image-editing method and apparatus, in which a personal contour extracted from image data is optimized, and then the brightness of the background region is adjusted.  
         [0111]     In addition, the present invention can provide various image-editing services which a user desires through the automated extraction of the contour.  
         [0112]     Furthermore, the present invention can provide a more discriminating image-editing service in a variety of devices which allow a user to store and view photographs and videos using an automated contour-extracting algorithm since it can be applied to a photo-browsing system.  
         [0113]     Although a few embodiments of the present invention have been shown and described, the present invention is not limited to the described embodiments. Instead, it would be appreciated by those skilled in the art that changes may be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.