Methods and systems for tracking image senders using client devices are described herein. A computing system may receive an image containing a first watermark vector corresponding to a user account of an image sender. The computing system may convert the image to a frequency domain image that contains the first watermark vector. From the frequency domain image, the computing system may identify the first watermark vector. The computing system may compare the first watermark vector to each of a plurality of stored watermark vectors, each corresponding to a known user account, to determine a probability of a match. The computing system may determine the user account of the sender of the image by determining which of the plurality of stored watermark vectors has a highest probability of a match, and may send, to a workplace administrator platform, an indication of the user account.

Methods, apparatus, systems, and articles of manufacture are disclosed to perform time alignment for watermarks. An example apparatus adjusts a power value of an element of a template based on respective average magnitudes and respective tonality ratios corresponding to a plurality of frequency representations of a media signal, the media signal to be encoded with at least one watermark, the element corresponding to one of the plurality of frequency representations. Additionally, the example apparatus computes an alignment of the template to the media signal based on respective power values of elements of the template, the template corresponding to a type of the at least one watermark. The example apparatus also encodes the media signal with the at least one watermark according to the alignment.

This disclosure relates to image signal processing technology including signal encoding. One claim recites a method of detecting plural-bit code conflicts within an image, the image includes at least one color separation. The image includes a first plural-bit code carried by a first symbology, and a second plural-bit code carried by a second symbology, the first symbology and the second symbology comprising different symbology types. The method includes: accessing a subset of the image that comprises the first plural-bit code carried by the first symbology; analyzing the subset of the image to decode the first plural-bit code; analyzing the at least one color separation to spatially locate and decode the second plural-bit code carried by the second symbology; comparing the first plural-bit code and the second plural-bit code; and outputting information if a conflict is identified by said act of comparing, in which the information comprises a spatial location within the image of the conflict. Of course, other claims, features and combinations are described as well.

A secure image for a security document is generated by performing a rasterization process for each of a plurality of mono-color base images using a plurality of different threshold functions. For each base image, the plurality of threshold functions cover different intensity regions and result in a complex rasterization pattern depending on the intensity of the input image. The resulting binary images obtained by the rasterization process are combined using offset printing with fluorescent inks of different colors, to result in a multi-color fluorescent output image including a plurality of different complex rasterization patterns.

Advanced signal processing technology including steganographic embedding and digital watermarking is described. For an encoded image, detectability measures can be generated including a first detectability measure associated with a synchronization component strength and a second detectability measure associated with a message component strength. Such measures can be used to help determine a likelihood that the encoded image, once printed on a physical substrate, will be detectable from optical scan data representing such. Of course, other features and combinations are described as well.

As image source attribution techniques have become significantly sophisticated and are now becoming commonplace, there is a growing need for capabilities to anonymize images and videos. Focusing on the photo response non-uniformity noise pattern based sensor fingerprinting technique, this work evaluates the effectiveness of well-established seam carving method to defend against sensor fingerprint matching. We consider ways in which seam-carving based anonymization can be countered and propose enhancements over conventional seam carving method. Our results show that applying geometrical distortion in addition to seam carving will make counter attack very ineffective both in terms of computational complexity and accuracy.

This disclosure relates to advanced signal processing technology including signal encoding. One combination includes an apparatus comprising: memory for storing image data, the image data comprising a plurality of color separations or channels, in which the image data comprises at least a first type of machine-readable symbology comprising a 1D barcode represented therein and a second type of machine-readable symbology comprising a first signal represented therein, in which the second type of machine-readable symbology comprises a different type of machine-readable symbology relative to the first type of machine-readable symbology, the 1D barcode comprising a first plural-bit code and the first signal comprising a second plural-bit code; a barcode reader configured to analyze the image data to decode the 1D barcode to obtain the first plural-bit code; a signal decoder configured to analyze one or more color separations or channels of the plurality of color separations or channels to decode the first signal to obtain the second plural-bit code; one or more processors configured to determine whether the second plural-bit code and the first plural-bit code conflict; and to identify a conflict based on a conflict determination. Of course, other features and combinations are described as well.

This disclosure relates to advanced signal processing technology including signal encoding. One combination includes an apparatus comprising: memory for storing image data, the image data comprising a plurality of color separations or channels, in which the image data comprises at least a first type of machine-readable symbology comprising a 1D barcode represented therein and a second type of machine-readable symbology comprising a first signal represented therein, in which the second type of machine-readable symbology comprises a different type of machine-readable symbology relative to the first type of machine-readable symbology, the 1D barcode comprising a first plural-bit code and the first signal comprising a second plural-bit code; a barcode reader configured to analyze the image data to decode the 1D barcode to obtain the first plural-bit code; a signal decoder configured to analyze one or more color separations or channels of the plurality of color separations or channels to decode the first signal to obtain the second plural-bit code; one or more processors configured to determine whether the second plural-bit code and the first plural-bit code conflict; and to identify a conflict based on a conflict determination. Of course, other features and combinations are described as well.

This disclosure relates to advanced signal processing technology including steganographic embedding and digital watermarking. One combination includes an image processing method comprising: obtaining data representing a digital image; using one or more processors, embedding an information signal within the data representing a digital image, the information signal comprising a synchronization component and a message component, said embedding yielding altered data; transforming the altered data to estimate a print and optical capture process, said transforming yielding transformed, altered data; for each of a plurality of regions within the transformed, altered data, generating detectability measures, in which a first detectability measure comprises a measure corresponding to synchronization component strength within region of the transformed, altered data, and in which a second measure comprises a measure corresponding to message component strength within the region of the transformed, altered data; based on a combination of the detectability measures from each of the plurality of regions, determining a likelihood that the altered data, once printed on a physical substrate, will be detectable from optical scan data representing such. Of course, other features and combinations are described as well.

Methods and systems for tracking image senders using client devices are described herein. A computing system may receive an image containing a first watermark vector corresponding to a user account of an image sender. The computing system may convert the image to a frequency domain image that contains the first watermark vector. From the frequency domain image, the computing system may identify the first watermark vector. The computing system may compare the first watermark vector to each of a plurality of stored watermark vectors, each corresponding to a known user account, to determine a probability of a match. The computing system may determine the user account of the sender of the image by determining which of the plurality of stored watermark vectors has a highest probability of a match, and may send, to a workplace administrator platform, an indication of the user account.