In this paper, an effective framework for passive-blind color image forgery detection is proposed. It is a combination of image features extracted from image luminance by applying a rake-transform and from image chroma by using edge statistics. The efficacy of the image features has been tested over two color image datasets established for tampering detection. The proposed framework outweighs the state of the arts over the small-scale dataset, and performs well on the newly established large-scaled dataset (likely the first reported test result on this dataset). The initial tests on some real image forgery cases available in the website and those reported in the literature on image composition with advanced image and vision technologies indicate the promise possessed as well as the challenge faced by the community of image forgery detection.