Abstract: A method, computer program product, and computer system for detection and utilization of similarities among tables in multiple data systems that include a first data system and a second data system. A semantic dataset is generated. A first measure (X) of similarity between semantic data in columns of the first and second data systems is computed using the semantic dataset. A first, different measure (Y) of similarity between semantic data in columns of the first and second data systems is computed using the semantic dataset. A third measure (Z) similarity between columns of the first and second data systems is computed based on data in cells within the columns. A weighted combination (U) of X, Y, and Z between the columns of tables in the first and second data systems is computed. X, Y, Z, U or combinations thereof are used to improve a computer system.

Abstract: A method, computer program product, and computer system for detection and utilization of similarities among tables in multiple data systems that include a first data system and a second data system. A semantic dataset is generated. A first measure (X) of similarity between semantic data in columns of the first and second data systems is computed using the semantic dataset. A first, different measure (Y) of similarity between semantic data in columns of the first and second data systems is computed using the semantic dataset. A third measure (Z) similarity between columns of the first and second data systems is computed based on data in cells within the columns. A weighted combination (U) of X, Y, and Z between the columns of tables in the first and second data systems is computed. X, Y, Z, U or combinations thereof are used to improve a computer system.

Abstract: Methods and systems for image binarization using mean restrain are disclosed. A method includes: obtaining, by a computing device, a grayscale image; generating, by the computing device, a histogram from the grayscale image; determining, by the computing device, a foreground mean value and a background mean value for each pixel value in the histogram; determining, by the computing device, a binarization threshold using the foreground mean values and the background mean values; and generating, by the computing device, a binarized image using the grayscale image and the binarization threshold.

Abstract: Methods and systems for image binarization using mean restrain are disclosed. A method includes: obtaining, by a computing device, a grayscale image; generating, by the computing device, a histogram from the grayscale image; determining, by the computing device, a foreground mean value and a background mean value for each pixel value in the histogram; determining, by the computing device, a binarization threshold using the foreground mean values and the background mean values; and generating, by the computing device, a binarized image using the grayscale image and the binarization threshold.