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An approach to dividing the printed circuit board into parts to increase visibility of defects in a PCB image is considered. The approach is based on a piecewise linear approximation of a cumulative histogram. The last one is calculated for numbers of informative pixels placed in rows and columns of an image matrix. Informative pixels are those indicating contacts and C traces. The histogram demonstrates a distribution of informative pixels along the OX and OY axes. The beginning and ending points of linear lines are taken as coordinates of the divided parts of the PCB board. The flood-fill algorithm is used to color and separate the PCB chains components. The start pixels are taken from a set of informative pixels. To measure defect values, a mean intensity and gradient functions for the template and manufactured images are used. Distributed cumulative histograms are applied to PCB components to detect places and intensity of defects.

The Ramer-Douglas-Peucker algorithm for piecewise approximation is used for image multilevel segmentation. The cumulative histogram is selected as a function for approximation. The algorithm allows you to determine threshold values of continuous and discrete images. The algorithm is used to separate cloudiness from background and to calculate cloudiness intensity. The found points of the approximated function have been accepted to change pixel intensity by proposed formulas. The algorithm efficiency is compared with those based on ordinary and cumulative histograms. By controlling the number of points for piecewise linear approximation function, the necessary segmentation accuracy can be achieved. The algorithm complexity is linear to the number of image pixels and to the number of intensity steps. The developed algorithm is applied to the satellite map images to separate clouds of different intensity. The extracted clouds of different intensity are used to classify regions by cloudiness with a developed clustering algorithm. Testing and experimental results are presented.

The algorithm of the dynamic threshold segmentation of images using clipping plane in a three-dimensional XYZ image space is proposed. To build the clipping plane of the dynamic threshold the precession and nutation angles as the base threshold values are found. The developed algorithm is applied to the satellite map images to get cloudiness intensity. The satellite map images are transformed by segmentation and inversion. The segmented and inverted images are scanned to receive the distributed cumulative histograms. By the help of so-called cloudiness meter the statistical data is processed for calculation and monitoring of cloudiness in Ukraine. The formulas to create an image of the distributed cumulative histogram are considered. Formulas to reconstruct images of the rotated satellite map images are proposed. The satellite weather map images were taken from the Wunderground services. The clustering algorithm is used to classify the regions of Ukraine by cloudiness intensity, which were created distributed cumulative images. The clustering algorithm is based on the agglomerative procedure.

An approach for decomposition of visual images by clustering and pattern classification by structure features is considered. Multilevel hierarchical clusters such as rectangles, closed regions and integrated areas are proposed. Hierarchically constructed fragments are material to form pattern structure features. To reduce the clustering algorithm complexity the tolerance coefficient and quality criteria for merging process are proposed. The results of pattern classification by structure features for some image groups by hand and automatic regimes are presented in the article. Hierarchical trees are got for different number of structure coefficients as well as for absolute and relative merging functions.

The paper contains research results of graphic file format influence on image structure, quantitative changes in structuring coefficients of clustered images, influence of deformation changes caused by destruction processes on image quality. Clustering package for visual black-white and grey patterns was taken as the main instrument for investigation.

An approach to determine structural integral and distributed image features on the basis of the “X-ray” algorithm from the perspective of the frontal plane XOZ or lateral plane YOZ is considered. The distributed structural features of segments are formed for the space of intensity. Segmentation is performed through splitting the image and space by intensity and coordinate values. The results of defined features and searching algorithm are presented.