1. A method for face detection in a digital image, comprising: selecting skin pixels in the digital image based on a first set of predetermined threshold value ranges for U and V chrominance value ranges in YUV space and a second set of predetermined threshold value ranges for normalized R and normalized G in RGB space and H, S and V in HSV space; classifying any unselected pixels in the digital image into bright pixels and dark pixels using thresholds on luminance value Y of each pixel; selecting skin pixels from the bright pixels based on a third set of threshold normalized R, normalized G values, and H, S, and V values; selecting skin pixels from the dark pixels based on a fourth set of threshold normalized R, normalized G values, and H, S, and V values; grouping all the selected skin pixels into windows of a predetermined window size of m×n; declaring any window having skin pixels that is more than or equal to a predetermined number of skin pixels as a skin window; forming candidate face regions by grouping the skin windows and assigning a face number derived from face number of neighboring skin windows; determining boundaries of candidate face regions by determining a face boundary in x, y space based on assigned face numbers with the formed candidate face regions; determining eye regions in the determined boundaries of candidate face regions using a combination of edge detection, an eye map and continuity in windows containing eye pixels, wherein the eye pixels are pixels which exceed the edge detection and eye mapping thresholds; and declaring each formed candidate face region as face, if the eye regions are determined in the formed candidate face region.