A computing device for performing biometric verification, comprising: a processor configured to: compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region, the test image data having been captured by a camera comprising a first spectral capture module and a second spectral capture module; compute a second feature distance between the registered image data of the human face in the first spectral region and test image data of the human face in a second spectral region, wherein the first and second spectral regions are such that the respective outputs of the first and second spectral capture modules exhibit detectable differences characteristic of human skin wherein the detectable differences may be unreproducible by spoofing objects not comprised of human skin; compute a test feature distance between the test image data of the human face in the first spectral region and the test image data of the human face in the second spectral region; determine , based on a predetermined relationship differentiating between real human face image data and spoofed human face image data, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face, wherein the predetermined relationship compares a linear combination of the first feature distance , second feature distance , and test feature distance to a threshold; and modify a behavior of the computing device based on whether the human face is determined to be the real human face or the spoofed human face; wherein computing the first , second , and test feature distances includes computing a respective pair of feature vectors, each feature vector encoding, for corresponding image data, a histogram of texture values. compute a first feature distance between registered image data of a human face in a first spectral region and test image data of the human face in the first spectral region, the test image data having been captured by a camera comprising a first spectral capture module and a second spectral capture module; compute a second feature distance between the registered image data of the human face in the first spectral region and test image data of the human face in a second spectral region, wherein the first and second spectral regions are such that the respective outputs of the first and second spectral capture modules exhibit detectable differences characteristic of human skin wherein the detectable differences may be unreproducible by spoofing objects not comprised of human skin; compute a test feature distance between the test image data of the human face in the first spectral region and the test image data of the human face in the second spectral region; determine , based on a predetermined relationship differentiating between real human face image data and spoofed human face image data, whether the human face to which the test image data in the first and second spectral regions corresponds is a real human face or a spoofed human face, wherein the predetermined relationship compares a linear combination of the first feature distance , second feature distance , and test feature distance to a threshold; and modify a behavior of the computing device based on whether the human face is determined to be the real human face or the spoofed human face; wherein computing the first , second , and test feature distances includes computing a respective pair of feature vectors, each feature vector encoding, for corresponding image data, a histogram of texture values. <EOS>