A histogram is a visual representation of the distribution of quantitative data. The term was first introduced by Karl Pearson. To construct a histogram...

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

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...

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

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...

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...

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...

are typically recommended to preserve the readability of the resulting histograms. An outline of the decomposition algorithm, which is readily available...

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

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

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...

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...

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...

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

an algorithm that employs the statistical properties of the images is histogram matching. This is a classic algorithm for color transfer, but it can suffer...

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

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

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...

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

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

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

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

as the bars may not accurately represent the data. In such cases, a histogram or box plot may be more appropriate. May be misleading: Bar charts can...

histogram medians can be far more efficient because it is simple to update the histogram from window to window, and finding the median of a histogram...

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...

distribution, or histogram. Histograms, even when made from the same record, are different for different class limits. The histogram can also be derived...