A histogram is a visual representation of the distribution of quantitative data. To construct a histogram, the first step is to "bin" (or "bucket") the...

photography, a color histogram is a representation of the distribution of colors in an image. For digital images, a color histogram represents the number...

processing, histogram matching or histogram specification is the transformation of an image so that its histogram matches a specified histogram. The well-known...

An image histogram is a type of histogram that acts as a graphical representation of the tonal distribution in a digital image. It plots the number of...

Histogram equalization is a method in image processing of contrast adjustment using the image's histogram. This method usually increases the global contrast...

Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization...

Histograms are most commonly used as visual representations of data. However, Database systems use histograms to summarize data internally and provide...

neurophysiology, peristimulus time histogram and poststimulus time histogram, both abbreviated PSTH or PST histogram, are histograms of the times at which neurons...

The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The...

image. The algorithm consists of two steps: creating a histogram and then rendering the histogram. First, one iterates a set of functions, starting from...

is equivalent to a globally optimal k-means performed on the intensity histogram. The extension to multi-level thresholding was described in the original...

In robotics, Vector Field Histogram (VFH) is a real time motion planning algorithm proposed by Johann Borenstein and Yoram Koren in 1991. The VFH utilizes...

A dose-volume histogram (DVH) is a histogram relating radiation dose to tissue volume in radiation therapy planning. DVHs are most commonly used as a plan...

Oracle Database (commonly referred to as Oracle DBMS, Oracle Autonomous Database, or simply as Oracle) is a proprietary multi-model database management...

Histogram of oriented displacements (HOD) is a 2D trajectory descriptor. The trajectory is described using a histogram of the directions between each two...

proximity mapping — of the keys. Another variant of bucket sort known as histogram sort or counting sort adds an initial pass that counts the number of elements...

Scott's rule is a method to select the number of bins in a histogram. Scott's rule is widely employed in data analysis software including R, Python and...

Sturges's rule is a method to choose the number of bins for a histogram. Given n {\displaystyle n} observations, Sturges's rule suggests using k ^ = 1...

classification; it has further been determined that when LBP is combined with the Histogram of oriented gradients (HOG) descriptor, it improves the detection performance...

Freedman–Diaconis rule can be used to select the width of the bins to be used in a histogram. It is named after David A. Freedman and Persi Diaconis. For a set of...

often preferred. Histogram: Gerald Appel referred to bar graph plots of the basic MACD time series as "histogram". In Appel's Histogram the height of the...

In image processing, the balanced histogram thresholding method (BHT), is a very simple method used for automatic image thresholding. Like Otsu's Method...

methods are used in industry including the maximum entropy method, balanced histogram thresholding, Otsu's method (maximum variance), and k-means clustering...

both a histogram, and a normal probability plot. Normal probability plot of a sample from a uniform distribution – it has an S shape. Histogram of a sample...

of the probability table, proposed by Marsaglia et al. as the square histogram method, avoids the computation of y by instead checking the condition...

given some observations. The simplest and most common approach uses histogram-based estimation, but other approaches have been developed and used, each...

the width of the interval. The total area of the histogram is equal to the number of data. A histogram may also be normalized displaying relative frequencies...

rather than uniform. Histogram specification transforms the red, green and blue histograms to match the shapes of three specific histograms, rather than simply...

Examples Cause-and-effect diagram Check sheet Control chart Histogram Pareto chart Scatter diagram Flow chart Run chart The seven basic tools of quality...

multicanonical ensemble (also called multicanonical sampling or flat histogram) is a Markov chain Monte Carlo sampling technique that uses the Metropolis–Hastings...