A printing apparatus is provided. The printing apparatus includes a processing circuitry configured to generate embedding data to be embedded in a print image to be printed out; divide the print image into two or more areas, and embed the embedding data in each of the two or more areas in such a way that placement of the embedding data is identical in each of the areas; and output the print image in which the embedding data is embedded.

A method of printing authentication indicia by applying an at least amplitude-modulated halftone print in a detection zone to an object uses adjoining halftone cells, in each of which a halftone dot is printed from a matrix of printable halftone elements, individual tone values of the halftone print corresponding in each case to a halftone plane of a halftone mountain for a halftone dot. In this process, the assigned screen plane of the screen mountain is modified in the detection zone in a predetermined manner for a plurality of tone values of screen dots to be printed, so that a predetermined matrix image of the screen elements to be printed is assigned to it while the tone value of the print remains constant.

Disclosed is an anti-counterfeiting and encryption method based on a local random image transformation technique, which belongs to the technical field of anti-counterfeiting and encryption. In the present disclosure, local replacement is performed on random images (that is, the arrangement structure of pixels in a space is changed or pixel values are changed), and then, two random images are used to store corresponding information; and “locally scrambled” portions of the images contain a part of key information. However, since the images are still random, there is still no explicit information display in the images; and even if the information is intercepted during a transfer process, the content of the information cannot be known without the original first random scatter plot, and the existing information also cannot be tampered with. In the present disclosure, a user does not need to memorize any password.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

Provided is a method of embedding and extracting watermark data that is robust against geometric distortion and low-quality photographing and for which the probability of successfully extracting watermark data for an original image is high, while the probability of successfully extracting the watermark data in the case of unauthorized copying is seriously impaired. The data embedding method according to an embodiment of the present invention comprises a step of converting the noise-based image using watermark data, and a step of adjusting the original image using the converted noise-based image.

An image reading apparatus compares a difference in luminance value between a pixel of interest in image information acquired via a reading unit and a pixel separated from the pixel of interest by a first distance with a first threshold value. Further, the image reading apparatus compares a difference in luminance value between the pixel of interest and a pixel present within a range to a pixel separated from the pixel of interest by a second distance that is larger than the first distance with a second threshold value. The image reading apparatus determines whether or not the pixel of interest is an edge pixel at an original end portion based on results of those comparisons, and determines an original size based on a result of the determination.