A multi-touch recognition apparatus comprising: a display panel to display an image; a camera unit to acquire an image to sense a user touch position on the display panel ; a storage unit to store a background image; and a controller configured to: perform blur filtering for noise removal when the image acquired by the camera unit is input, calculate a difference image obtained by removing the background image stored in the storage unit from the blur-filtered image, calculate an absolute value image obtained by converting pixel values of the difference image into absolute values, calculate a binary image obtained by binarization of the absolute value image, calculate a new background image using the difference image and the binary image, update the background image stored in the storage unit with the new background image, and calculate a threshold value in the calculation of the binary image using the following equation: Th = Mean I . + alpha ∗ std I . , wherein Th is the threshold value, Mean(I(.)) is the mean of the absolute value image of the difference image, alpha is a weight for distribution of pixel values of the image, and std(I(.)) is a standard deviation of the absolute value image of the difference image. a display panel to display an image; a camera unit to acquire an image to sense a user touch position on the display panel ; a storage unit to store a background image; and a controller configured to: perform blur filtering for noise removal when the image acquired by the camera unit is input, calculate a difference image obtained by removing the background image stored in the storage unit from the blur-filtered image, calculate an absolute value image obtained by converting pixel values of the difference image into absolute values, calculate a binary image obtained by binarization of the absolute value image, calculate a new background image using the difference image and the binary image, update the background image stored in the storage unit with the new background image, and calculate a threshold value in the calculation of the binary image using the following equation: Th = Mean I . + alpha ∗ std I . , wherein Th is the threshold value, Mean(I(.)) is the mean of the absolute value image of the difference image, alpha is a weight for distribution of pixel values of the image, and std(I(.)) is a standard deviation of the absolute value image of the difference image. perform blur filtering for noise removal when the image acquired by the camera unit is input, calculate a difference image obtained by removing the background image stored in the storage unit from the blur-filtered image, calculate an absolute value image obtained by converting pixel values of the difference image into absolute values, calculate a binary image obtained by binarization of the absolute value image, calculate a new background image using the difference image and the binary image, update the background image stored in the storage unit with the new background image, and calculate a threshold value in the calculation of the binary image using the following equation: Th = Mean I . + alpha ∗ std I . , wherein Th is the threshold value, Mean(I(.)) is the mean of the absolute value image of the difference image, alpha is a weight for distribution of pixel values of the image, and std(I(.)) is a standard deviation of the absolute value image of the difference image. <EOS>