US20140044308A1 - Image determining method and object coordinate computing apparatus - Google Patents

Image determining method and object coordinate computing apparatus Download PDF

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Publication number
US20140044308A1
US20140044308A1 US13/789,591 US201313789591A US2014044308A1 US 20140044308 A1 US20140044308 A1 US 20140044308A1 US 201313789591 A US201313789591 A US 201313789591A US 2014044308 A1 US2014044308 A1 US 2014044308A1
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Prior art keywords
row
specific image
pixels
pixel
range
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Abandoned
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US13/789,591
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English (en)
Inventor
Chia-Cheun LIANG
Shu-Sian Yang
Yi-Hsien Ko
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Pixart Imaging Inc
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Pixart Imaging Inc
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Assigned to PIXART IMAGING INC. reassignment PIXART IMAGING INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: KO, YI-HSIEN, LIANG, CHIA-CHEUN, YANG, SHU-SIAN
Publication of US20140044308A1 publication Critical patent/US20140044308A1/en
Priority to US15/212,281 priority Critical patent/US10255518B2/en
Abandoned legal-status Critical Current

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    • G06K9/62—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
    • G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding

Definitions

  • the present invention relates to an image determining method and an object coordinate computing apparatus, and particularly relates to an image determining method and an object coordinate computing apparatus, which utilize both brightness and conditions besides brightness to determine the predetermined image pixel or the object pixel.
  • FIG. 1 is a schematic diagram illustrating a prior art image determining method for determining an object coordinate in an image.
  • FIG. 1 is a gray level diagram of an image (i.e. an brightness diagram of an image), which is a 7 ⁇ 8 matrix having 7 ⁇ 8 pixels P 11 -P 78 .
  • the image includes a specific image generated by an object (in this example, a light source). Specific image pixels for this specific image have higher brightness values than the pixels surrounding them, for examples, pixels P 16 , P 25 , P 27 , P 34 , P 38 , P 43 , P 48 , P 54 , P 57 and P 65 -P 67 .
  • One of the methods for determining the specific image pixels is determining the pixels having brightness values higher than a threshold value as specific image pixels.
  • the threshold value is gray level 100 , such that the pixels P 26 , P 35 -P 37 , P 44 -P 47 , and P 55 -P 56 will be determined to be specific image pixels.
  • the edge pixels for the specific image have lower brightness values, thus such determining method still determines the pixels P 16 P 25 P 27 P 34 P 38 P 43 P 48 P 54 P 57 and P 65 -P 67 to be normal pixels rather than specific image pixels.
  • the threshold value is adjusted to be lower, such as 80, normal pixels P 75 and P 76 will be determined to be specific image pixels, but still exclude the pixel P 16 .
  • the size, location and brightness values of different specific images caused by different objects are all different, thus a most suitable brightness threshold value is hard to select.
  • One objective of the present invention is to provide an image determining method utilizing brightness and parameters besides brightness to determine specific image pixels or object pixels, and provides an object coordinate computing apparatus utilizing the image determining method.
  • One embodiment of the present invention discloses an image determining method, for determining which pixels in an image are specific image pixels of a specific image, comprising: (a) determining which pixels in the image have brightness values larger than a threshold value; (b) determining the pixels having brightness values larger than the threshold value as the specific image pixels; and determining pixels in a predetermined range of at least one the specific image pixel as the specific image pixels as well.
  • Another embodiment of the present invention discloses an image determining method, for determining which pixels in an image are specific image pixels of a specific image, comprising: (a) scanning pixels of at least one row in an image in turn, and determining which pixels in the row is larger than a threshold value; (b) determining at least one first row specific image pixel, which has a brightness value larger than a threshold value, in a first row to be the specific image pixel, and defines a specific image range according to the first row specific image pixel; and (c) determining a second row specific image pixel inside the range, which is located in the specific image range of a second row after the first row, to be the specific image pixel while scanning the second row.
  • Still another embodiment of the present invention discloses an object coordinate computing apparatus, comprising: a camera, for catching an image, which is a gray level diagram, for at least one object; a reading circuit, for scanning pixels of at least one row in the image in turn; for recoding brightness values and coordinates for the pixels; for defining an object range according to the brightness values and the coordinates for a first row of the rows; for determining first row object pixels in the object range of the first row to be the object pixels; and for determining a second row specific image pixel inside the range, which is inside the object range of a second row after the first row, to be the object pixel while scanning the second row; wherein the reading circuit utilizes the recorded brightness values and the recorded coordinate to compute a gravity center of the object.
  • the present invention provides an image determining method for determining specific image pixels or object pixels, an object coordinate computing method and an object coordinate computing apparatus, according to brightness and parameters besides brightness.
  • the prior art issue that only brightness is utilized for determining can be avoided.
  • different conditions can be set based on different object types and the size for caught images, such that the determining mechanism can be more accurate and can be set unlimitedly.
  • the gravity center of the object can be moved downward if the gravity center is computed according to the image determining mechanism of the present invention. By this way, the gravity center matches the habit for a user while handling a remote controller, such that the displacement detecting can be more accurate.
  • FIG. 1 is a schematic diagram illustrating a prior art image determining method for determining an object coordinate in an image.
  • FIG. 2 and FIG. 4 are schematic diagrams illustrating image determining methods according to embodiments of the present invention.
  • FIG. 3 and FIG. 5 are flowcharts illustrating image determining methods according to embodiments of the present invention.
  • FIG. 6 is a schematic diagram illustrating an object coordinate computing apparatus utilizing the image determining method shown in FIG. 2 to FIG. 5 .
  • FIG. 2 and FIG. 4 are schematic diagrams illustrating image determining methods according to embodiments of the present invention.
  • FIG. 2 illustrates a first embodiment while FIG. 4 illustrates a second embodiment.
  • FIG. 2 and FIG. 4 utilizes the gray level diagram which is the same as which in FIG. 1 , but it does not mean to limit the image determining method of the present invention is limited to this gray level diagram.
  • pixels in the image are determined that if any of them has a brightness value larger than a threshold value, and then the pixels having brightness values larger than the threshold value are determined as the initial specific image pixels.
  • specific image pixels including the initial specific image pixels are determined according to the initial specific image pixels.
  • the threshold value is determined to be 100 as shown in FIG. 1 , thus the pixels P 26 , P 35 -P 36 , P 44 -P 47 and P 55 -P 66 are determined to be the initial specific image pixels.
  • this step can be performed via scanning and determining in turn, but the determining step can be performed after all rows have been scanned.
  • the pixels in a predetermined range of the initial specific image pixels are determined to be specific image pixels.
  • each initial specific image pixel is utilized as a center of a 3 ⁇ 3 pixel matrix to generate a pixel matrix, which is utilized to define the predetermined range.
  • each pixel in the pixel matrix is determined to be the specific image pixel.
  • the pixel P 44 is utilized as a center of the 3 ⁇ 3 pixel matrix, which includes pixels P 33 -P 35 , P 43 -P 45 , and P 53 -P 55 . These pixels are all determined to be specific image pixels.
  • pixels P 35 , P 44 -P 45 , and P 55 are all determined to be initial specific image pixels in the previous step, thus the step of utilizing the pixel P 44 as a center of the pixel matrix adds the pixels P 33 -P 34 , P 43 , and P 53 -P 55 to the group of specific image pixels.
  • pixels P 54 , and P 64 -P 65 are added to the group of specific image pixels. If the same steps are performed for pixels P 26 , P 35 -P 36 , P 44 -P 47 and P 55 -P 66 , pixels P 15 -P 17 P 24 -P 25 P 27 P 33 -P 34 P 37 -P 38 P 43 P 48 P 53 -P 54 P 57 -P 58 and P 64 -P 67 are added to the group of specific image pixels.
  • the above-mentioned predetermined range is not limited to a pixel matrix with the same width and length, and is not limited to a pixel matrix as well.
  • This predetermined range can be set according to other parameters, such as an image of the object type that is desired to be determined.
  • the initial specific image pixels and the specific image pixels determined according to the initial specific image pixels are both specific image pixels and have no difference. The reason for giving them different names is to make them more easily to be distinguished such that the concept of the present invention can be depicted for more clearly.
  • the image determining method shown in FIG. 3 can be acquired according to the first embodiment shown in FIG. 2 , which includes the following steps:
  • the predetermined range is a 3 ⁇ 3 pixel matrix such that the pixels P 15 -P 17 P 24 -P 25 P 27 P 33 -P 34 P 37 -P 38 P 43 P 48 P 53 -P 54 P 57 -P 58 and P 64 -P 67 , which are not initial specific image pixels, are also determined to be specific image pixels.
  • pixels of at least one raw in an image are scanned in turn and determined which pixels have brightness values larger than a threshold value.
  • the direction for scanning is downward. That is, pixels P 71 -P 78 are scanned first, then the pixels P 61 -P 68 are scanned, then the pixels P 61 -P 68 are scanned . . . and so on.
  • any one row of the image (the first one row L 1 in this embodiment) is determined to include at lease one pixel having a brightness value larger than a threshold value such as pixels P 55 , P 56 (named first row specific image pixels)
  • the first row specific image pixels are determined as specific image pixels and a specific image range W 1 is defined according to the first row specific image pixels.
  • the leftmost pixel and the rightmost pixel of the first row specific image pixels are utilized to define edges of the specific image range W 1 , but it is not limited.
  • the image pixels in the specific image range W 1 of the next row are all determined to be specific images pixels while scanning the next row.
  • the pixels P 45 , P 46 in the specific image range W 1 of the second row L 2 are determined to be specific images pixels, which are called second row specific image pixels inside the range, while scanning the second row L 2 including pixels P 41 -P 48 .
  • Pixels of the second row outside the specific image range W 1 are also determined to check if they have brightness values larger than the threshold value. If all the brightness values are less than the threshold value, the specific image range W 1 is kept, and the pixels in the specific image range W 1 are determined to be specific image pixels while scanning the rows after the second row. If at least one pixel located outside the specific image range W 1 of the second row, which is named a second row specific image pixel outside the range, has a brightness value larger than the threshold value, the second row specific image pixel outside the range is determined to be a specific image pixel. Additionally, the specific image range W 1 is updated according to the second row specific image pixel outside the range. The pixels in the updated specific image range of the next row are determined to be the specific image pixel while scanning the next row.
  • the second row specific image pixels outside the range P 44 , P 47 which are located outside the predetermined image range W 1 , have brightness values larger than the threshold value 100
  • the second row specific image pixels outside the range P 44 , P 47 are also determined to be specific image pixels and the specific image range W 1 is updated to be the specific image range W 2 .
  • the third row specific image pixels inside the range P 34 -P 37 which are located inside the specific image range W 2 of the third row L 3 , are determined to be the specific image pixels while scanning the third row L 3 .
  • the pixels P 31 -P 33 , P 38 outside the specific image range W 2 of the third row L 3 are determined to check if they have brightness values larger than the threshold value.
  • the brightness values of the pixels P 31 -P 33 , P 38 are not larger than 100, thus the specific image range W 2 is kept.
  • the above-mentioned steps are performed while scanning the fourth row L 4 , thus the pixels P 24 -P 27 inside the specific image range W 2 are determined to be the specific image pixels and the specific image range W 2 is kept.
  • the pixels P 14 -P 17 inside the specific image range W 2 are determined to be the specific image pixels while scanning the fifth row L 5 .
  • the step for scanning this object and the step for updating the specific image range stop since no pixels in the fifth row L 5 have brightness values larger than the threshold value.
  • the mechanism for stopping the scanning step and the updating step can be triggered via various kinds of methods.
  • the scanning step and the updating step are stopped.
  • the scanning step and the updating step are stopped.
  • an image may include more than one objects, therefore the next object may be scanned and the above-mentioned steps are repeated if the scanning steps for one object has been stopped. Therefore, more than one object can be detected while scanning an image.
  • the objects can be distinguished from each other depending on space relations if two objects are on one row.
  • the scanning step of one object is stopped if all pixels of a whole row have brightness values smaller than the threshold value.
  • the scanning step of the other object is stopped if all pixels in a specific image range of a row have brightness values smaller than the threshold value.
  • an image determining method shown in FIG. 5 can be acquired, which includes following steps:
  • FIG. 6 is a schematic diagram illustrating an object coordinate computing apparatus 601 utilizing the image determining method shown in FIG. 2 to FIG. 5 .
  • the coordinate computing apparatus 601 is included in a displacement detecting system 600 .
  • the displacement detecting system 600 is only for example, the coordinate computing apparatus 601 can also be applied to other systems or apparatuses.
  • the displacement detecting system 600 includes an object coordinate computing apparatus 601 and a display 603 .
  • the display 603 includes a light source 605
  • the object coordinate computing apparatus 601 includes a camera 607 and a reading circuit 608 .
  • the camera 607 catches an image, which is a gray level diagram, for at least one object (the light source 605 in this embodiment).
  • the reading circuit 608 scans pixels of at least one row in an image in turn, and records brightness values and coordinates for the pixels.
  • the reading circuit 608 can perform the first embodiment shown in FIG. 2 and the second embodiment shown in FIG. 4 to determine which pixels are object pixels (i.e. the specific image pixels). Then the reading circuit 608 utilizes the recorded brightness values and the recorded coordinate to compute a gravity center of the light source 605 .
  • the reading circuit 608 utilizes the brightness of the object pixels as weighting, and computing the gravity center of the object via multiplying the weight and the coordinates of the object pixels.
  • the coordinate computing apparatus 601 can further include a processor (not illustrated) to compute a displacement between the object coordinate computing apparatus 601 and the display referring to the light source 605 . The processor further controls a cursor Cr according to the displacement.
  • the following object coordinate computing method can be acquired: (a) determining which pixels in the image have brightness values larger than a threshold value; (b) determining the pixels having brightness values larger than the threshold value as the object pixels of the object (such as pixels P 26 , P 35 -P 36 , P 44 -P 47 and P 55 -P 56 ); and (c) determining pixels in a predetermined range of at least one the object pixel as the object pixels as well; and (d) computing a coordinate of the object according to the determining result of the steps (b) and (c).
  • the following object coordinate computing method can be acquired: (a) scan pixels of at least one row in an image in turn, and determine which pixels in the row is larger than a threshold value; (b) determine at least one first row object pixel (such as P 55 , P 56 ), which has a brightness value larger than a threshold value, in a first row (Such as L 1 in FIG. 4 ) to be the object pixel, and defines a object range such as W 1 according to the first row object pixel; (c) determine a second row object pixel inside the range (such as P 45 , P 46 ), which is located in the object range of a second row (such as L 2 in FIG. 4 ) after the first row, to be the object pixel while scanning the second row; and (d) computing a coordinate of the object according to the determining result of the steps (b) and (c).
  • the present invention provides an image determining method for determining specific image pixels or object pixels, an object coordinate computing method and an object coordinate computing apparatus, according to brightness and parameters besides brightness.
  • the prior art issue that only brightness is utilized for determining can be avoided.
  • different conditions can be set based on different object types and the size for caught images, such that the determining mechanism can be more accurate and can be set unlimitedly.
  • the gravity center of the object can be moved downward if the gravity center is computed according to the image determining mechanism of the present invention. By this way, the gravity center matches the habit for a user while handling a remote controller, such that the displacement detecting can be more accurate.
US13/789,591 2012-08-08 2013-03-07 Image determining method and object coordinate computing apparatus Abandoned US20140044308A1 (en)

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US10255518B2 (en) 2019-04-09
TW201407543A (zh) 2014-02-16
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US20160364627A1 (en) 2016-12-15

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