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'Picture' is a more general term that can refer to any visual representation, while 'photo' specifically refers to a photograph, which is an image captured using a camera.

To compare two images, we use the Mean Square Error (MSE) of the pixel values of the two images. Similar images will have less mean square error value. Using this method, we can compare two images having the same height, width and number of channels.

A visual diff finds differences between two files by eyeball search. The term optical diff has also been reported, and is sometimes more specifically used for the act of superimposing two nearly identical printouts on one another and holding them up to a light to spot differences.

Understanding Image Comparison When comparing two images, you typically want to measure the similarity between them. This similarity can be quantified using various metrics, such as mean squared error (MSE), structural similarity index (SSIM), or perceptual hashing algorithms like pHash or dHash.

Considering the image as a matrix we can compare pixel by pixel with a simple double construct for (pixel_image[r:rows][c:columns] == pixel_image2[r:rows][c:columns] only if the "pixel" is considered as integer.

The image difference of two images is defined as the sum of the absolute difference at each pixel.

In 1.5 minutes be ready to compare and contrast the two photographs: give a brief description of the two photos (action, location) say what the pictures have in common. say what in what way the pictures are different. say which of the activities presented in the pictures you'd prefer. explain why.

Image Compare is a lightweight, standalone and offline application to visually compare a pair of images and highlight the differences between them.