Source: http://www.google.com/patents/US5887082?dq=georgia+pacific+dispenser&ei=3350T6jaCc-q0AHQucGAAw
Timestamp: 2014-03-16 01:59:38
Document Index: 629532283

Matched Legal Cases: ['art 1', 'art 2', 'art 1', 'art 2', 'application No. 08', 'application No. 08', 'application No. 08']

Patent US5887082 - Image detecting apparatus - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsAn image area extracting method for extracting the desired areas from the image accurately and efficiently. The rough boundary area, in which the boundary area is roughly assigned between the desired area and areas other than the desired area, is divided into a plurality of small areas. The area extracting...http://www.google.com/patents/US5887082?utm_source=gb-gplus-sharePatent US5887082 - Image detecting apparatusAdvanced Patent SearchPublication numberUS5887082 APublication typeGrantApplication numberUS 08/561,377Publication dateMar 23, 1999Filing dateNov 21, 1995Priority dateNov 29, 1994Fee statusPaidAlso published asUS6252985Publication number08561377, 561377, US 5887082 A, US 5887082A, US-A-5887082, US5887082 A, US5887082AInventorsTomoo Mitsunaga, Takashi TotsukaOriginal AssigneeSony CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (14), Non-Patent Citations (32), Referenced by (23), Classifications (13), Legal Events (5) External Links: USPTO, USPTO Assignment, EspacenetImage detecting apparatusUS 5887082 AAbstract An image area extracting method for extracting the desired areas from the image accurately and efficiently. The rough boundary area, in which the boundary area is roughly assigned between the desired area and areas other than the desired area, is divided into a plurality of small areas. The area extracting procedure is executed on each small area and the desired area and areas other than the desired area are detected from each small area. The boundary area mask image is formed based on the detection result and the desired area is extracted based on the boundary area mask image. Thus, the desired area can be extracted from the image accurately and efficiently.
What is claimed is: 1. An image area extracting method for extracting a desired area from an image, comprising the steps of:dividing rough boundary area image corresponding to said image, in which boundary area between said desired area and areas other than said desired area is roughly assigned, into a plurality of small areas; detecting the desired area and areas other than said desired area from said each small area by executing area extracting means to each of said small areas; and forming a boundary area mask image of said roughly assigned boundary area between said desired area and areas other than said desired area depending upon said detection result and extracting said desired area based on said boundary mask image, wherein said image area extracting processing comprises extracting the image area by utilizing an axis selection edge detecting process wherein edges of the desired area are detected by selecting an edge detection axis direction on the image and alternatively by selecting an edge detection axis direction on color space. 2. The image area extracting method according to claim 1, whereina parameter of one of said each area extracting means which is executed to said each small area of said detecting step can be adjusted, and the parameter adjusted for each small area is applied. 3. The image area extracting method according to claim 2, whereinat least one of said area extracting means of said detecting step is the processing of approximating color distribution obtained by distributing color information of designated pixel on color space with an ellipsoid and dividing the image area by dividing said color space using said ellipsoid. 4. The image area extracting method according to claim 1, whereinwhen there are at least two area extracting means which are executed to said each small area of said detecting step, an optimum area extracting means is selected for said each small area to execute the selected area extracting means for each small area. 5. The image area extracting method according to claim 4, whereina parameter of one of said each area extracting means which is executed to said each small area of said detecting step can be adjusted, and the parameter adjusted for each small area is applied. 6. The image area extracting method according to claim 5, whereinat least one of said area extracting means of said detecting step is the processing of approximating color distribution obtained by distributing color information of designated pixel on color space with an ellipsoid and dividing the image area by dividing said color space using said ellipsoid. 7. An image area extracting method for extracting a desired area from an image, comprising the steps of:dividing rough boundary area image corresponding to said image, in which boundary area between said desired area and areas other than said desired area is roughly assigned, into a plurality of small areas; detecting the desired area and areas other than said desired area from said each small area by executing area extracting means to each of said small areas; forming a boundary area mask image of said roughly assigned boundary area between said desired area and areas other than said desired area depending upon said detection result; forming a non-boundary area mask image of said areas other than said roughly assigned boundary area; extracting said desired area based on said boundary mask image; and synthesizing the boundary area mask image and the non-boundary mask image to form a synthesized mask image for assigning the desired area, wherein said image area extracting processing comprises extracting the image area by utilizing an axis selection edge detecting process wherein edges of the desired area are detected by selecting an edge detection axis direction on the image and alternatively by selecting an edge detection axis direction on color space. Description
Techniques to extract an object from an image are conventionally well-known as methods for special effects. The techniques to extract an object are the mask image hand painting (video mat) method, the method using chroma key processing and luminance key processing, and the rough contour assigning and thinning (Object Extracting Method for Image Mixing, by Seiki Inoue, The transactions of the Institute of Electronics, Information, and Communication Engineers D-II vol. j74-D-II pages 1411-1418, 1991).
Moreover, in the method of rough contour assigning and thinning, the rough area including the contour of the object is assigned by an operator to obtain the shape of object by thinning the rough area based on the intensity of edge so as to match this rough area to the contour of object automatically.
Accordingly, in these methods, it was only video mat method which was capable of extracting the object area accurately from the optional background. However, because the video mat method requires the process to assign the object area per one pixel, it requires much time and skill and there arises a problem that its operational efficiency is not favorable.
FIGS. 6A and 6B are block diagrams showing the processing flow at the non-boundary area mask forming unit;
FIGS. 9A, 9B, and 9C are schematic diagrams showing the processing flow in the case of applying the ellipsoid color space dividing method to the embodiment as object area extracting means;
FIGS. 11A, 11B, and 11C are schematic diagrams showing the processing flow in the case of using the axis selection on the image;
FIG. 13A, 13B, and 13C are schematic diagrams showing the processing flow in the case of using the axis section on color space.
In FIG. 1, 1 generally shows an object area extracting apparatus according to the embodiment of the present invention. As shown in FIG. 1, the object area extracting apparatus 1 consists of a boundary area dividing unit 2, a boundary area mask forming unit 3, a non-boundary area mask forming unit 4 and a synthesizing unit 5. The boundary area mask forming unit 3 is connected to the plural number of object area extracting means 6a, 6b, . . . . Each of the object area extracting means respectively have input means, which are not shown.
The boundary area mask forming unit 3 executes the object extracting process to each small area by using a proper means out of the object area extracting means 6a, 6b, . . . so as to form the mask of the entire boundary area and output to the synthesizing unit 5. At this point, the selection of the object area extracting means 6a, 6b, . . . depends on the outside input by, for example, the operator.
The control unit 31 controls the whole of the boundary area mask forming unit 3, and the processing procedure of the control unit 31 is shown in FIG. 5. The control unit 31 has two kinds of conditions, i.e., non-selection mode and selection mode. The non-selection mode is the mode which is selected when the image data input is updated in order to output the first result. The selection mode is the mode which executes the processing by the object area extracting means 6a, 6b, . . . to the optional block interactively. The control unit 31 executes the object area extracting processing in the selection mode to the blocks which need modification, depending upon the first result for the new image input in non-selection mode.
As shown in the non-selection mode 51 of FIG. 5, the control unit 31 firstly selects one of the object area extracting means 6a, 6b, . . . (update the object area extracting number at step SP11). In the non-selection mode, preset default object area extracting means is selected. Then, the block to be informed to the sampling unit 32 is updated (update the block number at step SP12). In the non-selection mode, all blocks are selected in order.
Then, the control unit 31 designates the block position to the sampling unit 32 and outputs the sampling command to sample the necessary areas from the image data and rough boundary area image (SP13). The sampling unit 32 extracts the block position area informed by the control unit 31 from the image data and the input rough boundary area image so as to form each block. Formed two blocks are sent out to one of the object area extracting means 6a, 6b, . . . through the switch 34 in order to be used in the object area extracting process (SP15).
Next, the control unit 31 informs the switch 34 of the selected object area extracting means 6a, 6b, . . . and the present mode to make the switch 34 execute the object area extracting process. More specifically, the switch 34 which is an interface to each object area extracting means 6a, 6b, . . . outputs two blocks as operation mode (non-selection mode or selection mode) and input data to the selected object area extracting means 6a, 6b, . . . . Also the switch 34 receives the object area extraction result from the object area extracting means 6a, 6b, . . . and outputs the result and the block position information to the mask forming unit 33.
FIGS. 6A and 6B are the figures for describing the determination in the inside area of boundary area. In the non-boundary area mask forming unit 4, the mask image of which the outside of boundary area is α=0, the inside of boundary area is α=1, and the boundary area is indefinite (for convenience, α=0.5) is formed.
Then, at step SP33, by using the ellipsoid approximation means described above, ellipsoids for respective two areas are decided as shown in FIG. 9B. Thus, color space is divided into the object area (α=1), the background area (α=0) and the boundary area (0&lt;α&lt;1).
Thereafter, proceeding to step SP34, as shown in FIG. 9C, each pixel is distinguished as to which area of the object area, the background area, and the boundary area it belongs to, and α value of each pixel is output as a result of extraction, and the processing is terminated at step SP35. If the pixel belongs to the boundary area, α value is calculated according to the position relation to two ellipsoids.
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