An apparatus for detecting a motion mask includes: an image processor configured to generate a plurality of image frames; a first motion mask detector configured to detect at least one first motion mask by calculating a local feature of each pixel included in a partial or entire area of at least one current image frame which indicates a pixel value relationship between the each pixel and at least one neighboring pixel, and comparing the calculated local feature with a local feature of a corresponding pixel of at least one previous image frame; a second motion mask detector configured to detect at least one second motion mask based on a difference between the partial or entire area of the current image frame and a corresponding area of the previous image frame; and a motion mask generator configured to generate a final motion mask comprising at least one of the first motion mask and the second motion mask.

A method includes receiving image data corresponding to an image and determining object quality values based on a portion of the image data. The portion corresponds to an object represented in the image. The method also includes accessing object category metrics associated with an object category corresponding to the object. The method includes generating a notification indicating that the image data has been altered in response to a result of a comparison of the object quality values to the object category metrics. The result indicates alteration of the portion of the image data.

Systems and methods for image processing may perform one or more operations including, but not limited to: receiving raw image data from at least one imaging device; computing at least one image depth distance from the raw image data; computing one or more image validity flags from the raw image data; generating at least one data validity mask from the one or more image validity flags; determining a background imagery estimation from at least one image depth distance; generating at least one foreground mask from the background imagery estimation and the at least one image depth distance; generating at least one region-of-interest mask from the data validity mask and the foreground mask; and generating filtered raw image data from the raw image data and at least one region of interest mask.