Quantitative histogram analysis of images

A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed.Program summaryTitle of program: HAWGCCatalogue identifier: ADXG_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputers: Mobile Intel Pentium III, AMD DuronInstallations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engineOperating systems or monitors under which the program has been tested: WindowsME/2000/XPProgramming language used: LabVIEW 7.0Memory required to execute with typical data:  ∼16MB for starting and ∼160MB used for loading of an imageNo. of bits in a word: 32No. of processors used: 1Has the code been vectorized or parallelized?: NoNo of lines in distributed program, including test data, etc.:138 946No. of bytes in distributed program, including test data, etc.:15 166 675Distribution format: tar.gzNature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user.Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels.Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis)Typical running time: Seconds (depending on image size and processor speed)Unusual features of the program: None