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Using Exponential Fitting Function for Color Digital Image Edges Detection | ||
| Journal of College of Education | ||
| Article 1, Volume 0, Issue 1, 2017, Pages 113-130 | ||
| Authors | ||
| Ahmed Assal G. Al-Quraishi; Ali Abid D. Al-Zuk; Sabah Taufik A. Al-Chalabi | ||
| Abstract | ||
| The relationship of the local image elements in homogeneous regions of the image, approaches to the exponential distribution when we systemize these elements by increasing or decreasing manner. Therefore, we depended this property for recognition of the edge regions from homogeneous regions, this done via using least square algorithm to fit image data. Then calculate summation of the differences between the real values y(x) and the approximated values Y(x) from the exponential function. Where the small differences are verified in the homogeneous regions of the image where the values of y(x) approach from Y(x) values, while the high differences are verified in the non-homogeneous regions (edge regions). Here we can depend on these differences in the edges recognition. We depend this algorithm to detect the edges for the color image after analysis it to its bands (Red, Green, Blue, and Luminosity). Then apply fitting algorithm for each band then calculate the differences to each band and determine the mean value for the four differences in order to compare it with the threshold to determine the center element of the mask as an edge or not. The result of this algorithm produced accurate and good edges for different color images. Key Words: Adaptive edge detection, exponential fitting, least square curve fitting, fitting algorithm, exponential equation, regression, color edge. | ||
| Keywords | ||
| Adaptive edge detection; exponential fitting; least square curve fitting; fitting algorithm; exponential equation; regression; color edge | ||
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