Bad pixels are defined as those pixels showing a temporal evolution of the signal different from the rest of the pixels of a given array. Principal component analysis helps us to understand the definition of a statistical distance associated with each pixels, and using this distance it is possible to identify those pixels labeled as bad pixels. The spatiality of a pixel is also calculated. An assumption about the normality of the distribution of the distances of the pixels is revised. Although the influence on the robustness of the identification algorithm is negligible, the definition of a parameter related with this nonnormality helps to identify those principal components and eigenimages responsible for the departure from a multinormal distribution. The method for identifying the bad pixels is successfully applied to a set of frames obtained from a CCD visible and a focal plane array (FPA) IR camera.