A computer-implemented method for identifying a pore color of at least one skin pore, comprising the steps: • obtaining at least one image of a subject, wherein the step of obtaining the at least one image further comprises a step of performing histogram equalization to the obtained image to obtain a histogram-equalized image; wherein the step of obtaining the at least one image further comprises a step of filtering the histogram-equalized image or filtering the at least one image for removing one or more skin features that is not a skin pore to obtain a filtered image, wherein the one or more skin features is selected from the group consisting of shine, line, spot, hair, mole, pimple, acne, blackhead, and whitehead, and combinations thereof; wherein the step of filtering comprises using a frequency filter, wherein the frequency filter is selected from the group: a Fast Fourier Transformation filter and Band Pass filter, a Difference of Gaussian filter, and any combinations thereof; • extracting a pore image from the obtained image, wherein the extracted pore image identifies a boundary of the at least one skin pore ; comprising the steps of • superimposing the obtained image and the extracted pore image to identify the pore color within the identified boundary of the at least one skin pore. • defining an adjacency area radially from the identified boundary of the at least one skin pore; • superimposing the obtained image and the defined adjacency area to identify an adjacency area color; and • comparing the identified pore color to the identified adjacency area color to determine a pore color contrast value. • obtaining at least one image of a subject, wherein the step of obtaining the at least one image further comprises a step of performing histogram equalization to the obtained image to obtain a histogram-equalized image; wherein the step of obtaining the at least one image further comprises a step of filtering the histogram-equalized image or filtering the at least one image for removing one or more skin features that is not a skin pore to obtain a filtered image, wherein the one or more skin features is selected from the group consisting of shine, line, spot, hair, mole, pimple, acne, blackhead, and whitehead, and combinations thereof; wherein the step of filtering comprises using a frequency filter, wherein the frequency filter is selected from the group: a Fast Fourier Transformation filter and Band Pass filter, a Difference of Gaussian filter, and any combinations thereof; wherein the step of obtaining the at least one image further comprises a step of filtering the histogram-equalized image or filtering the at least one image for removing one or more skin features that is not a skin pore to obtain a filtered image, wherein the one or more skin features is selected from the group consisting of shine, line, spot, hair, mole, pimple, acne, blackhead, and whitehead, and combinations thereof; wherein the step of filtering comprises using a frequency filter, wherein the frequency filter is selected from the group: a Fast Fourier Transformation filter and Band Pass filter, a Difference of Gaussian filter, and any combinations thereof; • extracting a pore image from the obtained image, wherein the extracted pore image identifies a boundary of the at least one skin pore ; comprising the steps of • superimposing the obtained image and the extracted pore image to identify the pore color within the identified boundary of the at least one skin pore. • defining an adjacency area radially from the identified boundary of the at least one skin pore; • superimposing the obtained image and the defined adjacency area to identify an adjacency area color; and • comparing the identified pore color to the identified adjacency area color to determine a pore color contrast value. <EOS>