Figure-4: Binary Pattern with CoM at (6,8) The centre of mass for the test pattern (figure-3) comes out to be at location (6,8) and marked as white in figure-4 given below. of matrix elements with zero value.įrom figure-3, the centre of mass is given by the followings: (R i, C i) are the i th pixel coordinate of the pattern i.e. Where (R CoM, C CoM) are the row and column coordinate of the centre of mass of the pattern under test. The first order moments are computed by using the following equations: the pixels with black in color or the matrix elements with zero value. The centre of mass of the pattern under test is computed using the first order moments of the Cartesian coordinates of the pattern’s pixels i.e. The imread() function enables to have the binary image pattern in row x column matrix of ‘0’ and ‘1’ as black and white pixels. This task is performed by using the imread() function in matlab. The binary image pattern (figure-3) is scanned from left to right and top to bottom i.e. Figure-2: Grey Pattern Figure-3: Binary Pattern The equivalent binary pattern is shown in figure-3. The grey pattern can be binarized using the Otsu algorithm. It is converted to binary pattern as shown in figure-3.
Figure-1: Image as matrix of Rows and ColumnsĪ grey color pattern of size 7×5 is shown in figure-2. An example pixel at location (3,7) is shown as F(3,7). The pixel at (0,0) location is at top left corner of the image (refer to figure-1). In matlab IDE, the image dimensions are taken as row x column.
Black and white colors are attributed as 0 and 1 respectively (binary form) in digital image processing.
pattern as in black on a white color background or vice versa. For all, very firstly the pattern is converted to a binary class i.e. The centre of mass of a binary pattern is computed using the first order moments of the pattern pixel’s Cartesian Coordinates. The pattern’s shape and size can be estimated using the radii profile that is computed around the centre of mass. Project Manager, R&D at C-DACĮxtraction of centre of mass of a binary pattern is an important task in pattern recognition area in digital image processing domain.
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