The scharr kernel is obtained by minimizing angular error hence are more consistent and reduce artifacts. The sign of local gradient can be augmented with the edge information to make it more discriminative and robust. Hence the proposed SLG based transformation uses this information to calculate a 8-bit code for every pixel. The Scharr x and y derivative kernels are used to extract x and y-direction derivatives of eight neighboring pixels to obtain vcode and hcode, respectively.
The sign of local gradient (SLG) based transformation calculates sign_code for each pixel using the derivatives of its eight neighborhood. The sign_code for any pixel is a 8-bit binary number whose ith bit is defined as
equation(1)
View the MathML source
Turn MathJax on
where View the MathML source are the gradient of eight neighboring pixels centered at pixel Pj,k obtained by applying appropriate x or y direction Scharr kernel. The vcode or hcode for any image P can be obtained by evaluating sign_code for all pixel of that image. Every ROI is transformed into its corresponding vcode and hcode (as shown in Fig. 6). The basic assumption is that the pattern of edges within eight neighborhood of any pixel does not change abruptly, hence in sign_code of any pixel, only the sign of the derivative in its neighborhood is considered. This property ensures robustness of the proposed representation in illumination varying environments as it only uses the sign of the local gradient.