**1.3 Digital images creation in photo cameras**

The image on a photosensitive matrix of a photocamera is formed after light passage through a lens and the blurring filter (LF-filter), further postprocessing of digital signal received from a matrix [21]. At the analysis of the given circuit it is possible to select the following main sections of a recording path in digital photographic cameras which can be used for identification on a basis of features induced in resultant images [22]. The lens and bayonet joint form identifiable signs (low-frequency defects of the image, vignetting). Usage of the given signs for the automated and automatic identification is inconvenient in view of complexity of their extraction from context and built-in compensating circuits and algorithms in a majority of the modern cameras.

LF-filter ("blurring filter") is applied to lower moire formed due to space sampling by a photomatrix of image components with frequencies near and above Nyquist frequency. The filter forms average and high-frequency stable signs (the shade of the settled dust, filter spot defects). In view of it placement and, in most cases, impossibility of replacement, the features imported by it, are similar to the signs imported by the matrix. The photosensitive matrix unit with ADC forms stable signs in broad band of frequencies (additive and multiplicative noise of a matrix, defects of sensor elements - pointwise, cluster, column, line). In the majority of digital photocameras for color image forming the Bayer's [7] method is used, thus there is only one photosensitive sensor before which the lattice color filter (color filter array - CFA) is placed. Bayer's grid uses layout of filters of three primary colors allocated shown on a picture 1.3, where *R*, *G* and *B* accordingly filters of red, green and blue colors. The number of pixels with filters of green color is twice more than number of pixels for red and blue components, that reflects spectral sensitivity features of a human eye. Along with base Bayer pattern there is a set of other variants of a Bayer's matrix, created for the purpose of increasing sensitivity and color rendition accuracy, generally reached at the expense of space resolution of chromaticity.

Algorithms of interpolation form average and high-frequency features (correlative dependences of adjacent pixels, context-dependent interpolation heuristics).

The non-linear processing including noise reduction, color correction, levels correction (brightness, saturation, contrast). Forms low-frequency (gamma correction) and highfrequency (increase of contour sharpness), equalizing.

Compression stage features at the given stage are features of a used format (JPEG or other) such as specific quantization matrixes, a set and placement of the metadada fields.

In the most general case for the analysis of the image received from the real camera, the only accessible image is image in one of storage formats with lossy compression. On occasion (cameras of the upper consumer segment, semiprofessional and professional) also the RAWversion of the image subjected to correction of matrix defects, or compressed by lossless compression methods (TIFF) the image which has transited all steps of processing, except compression with quality loss can be the accessible.

Thus it is possible to formulate the requirements necessary for practically applicable systems of image identification:

302 Applications of Digital Signal Processing

Besides it, embedding worsens consumer characteristics of received record that is not always tolerable, and, at special importance of originality of digital record, can be

Other way of authenticity ascertainment is identification on the basis of recording path

The image on a photosensitive matrix of a photocamera is formed after light passage through a lens and the blurring filter (LF-filter), further postprocessing of digital signal received from a matrix [21]. At the analysis of the given circuit it is possible to select the following main sections of a recording path in digital photographic cameras which can be used for identification on a basis of features induced in resultant images [22]. The lens and bayonet joint form identifiable signs (low-frequency defects of the image, vignetting). Usage of the given signs for the automated and automatic identification is inconvenient in view of complexity of their extraction from context and built-in compensating circuits and

LF-filter ("blurring filter") is applied to lower moire formed due to space sampling by a photomatrix of image components with frequencies near and above Nyquist frequency. The filter forms average and high-frequency stable signs (the shade of the settled dust, filter spot defects). In view of it placement and, in most cases, impossibility of replacement, the features imported by it, are similar to the signs imported by the matrix. The photosensitive matrix unit with ADC forms stable signs in broad band of frequencies (additive and multiplicative noise of a matrix, defects of sensor elements - pointwise, cluster, column, line). In the majority of digital photocameras for color image forming the Bayer's [7] method is used, thus there is only one photosensitive sensor before which the lattice color filter (color filter array - CFA) is placed. Bayer's grid uses layout of filters of three primary colors allocated shown on a picture 1.3, where *R*, *G* and *B* accordingly filters of red, green and blue colors. The number of pixels with filters of green color is twice more than number of pixels for red and blue components, that reflects spectral sensitivity features of a human eye. Along with base Bayer pattern there is a set of other variants of a Bayer's matrix, created for the purpose of increasing sensitivity and color rendition accuracy, generally reached at the

Algorithms of interpolation form average and high-frequency features (correlative

The non-linear processing including noise reduction, color correction, levels correction (brightness, saturation, contrast). Forms low-frequency (gamma correction) and high-

Compression stage features at the given stage are features of a used format (JPEG or other)

In the most general case for the analysis of the image received from the real camera, the only accessible image is image in one of storage formats with lossy compression. On occasion (cameras of the upper consumer segment, semiprofessional and professional) also the RAWversion of the image subjected to correction of matrix defects, or compressed by lossless compression methods (TIFF) the image which has transited all steps of processing, except

Thus it is possible to formulate the requirements necessary for practically applicable systems

such as specific quantization matrixes, a set and placement of the metadada fields.

dependences of adjacent pixels, context-dependent interpolation heuristics).

inadmissible.

features, which are presented in a digital record.

**1.3 Digital images creation in photo cameras** 

algorithms in a majority of the modern cameras.

expense of space resolution of chromaticity.

frequency (increase of contour sharpness), equalizing.

compression with quality loss can be the accessible.

of image identification:


Thus, for digital photocameras it is possible to select two classes of features which could be used as a basis for identification:


In view of that algorithms of postprocessing are the general sometimes for all models of one vendor [16, 23], for detection by sample-unique features it is necessary to take identification on parameters of an analog section, i.e. on the first class of features.
