What is Segmentation

Grouping individuals according to the similar properties.

The division of the market into smaller groups, identified by certain common needs and desires, which require distinct marketing efforts.

Segmentation in image processing is the process of dividing an image into meaningful and distinct regions or segments based on certain characteristics or features. The goal is to simplify the representation of an image or make it more meaningful for analysis. Segmentation is commonly used in computer vision, medical imaging, and object recognition. Techniques include thresholding, region-based methods, and edge detection to identify and delineate different objects or regions within an image.

Is the process of classifying and partitioning a digital image, or point cloud, into multiple segments.

The process of dividing a market into clearly identifiable sub-segments with similar needs or wants.

Segmentation is the process of stratifying the portfolio (product, market, channel etc.) into clusters based on attributes like risk, margins, criticality, revenue, volume, lead times, life cycle stage, etc., which helps the organization put more emphasis and resources on key customers and products and make decisions on product portfolio management, as well as entry/exit of markets to enable an organization to offer differentiated service treatment to certain groups.

It is usually the first stage of image analysis. Image segmentation can be described as dividing an image into meaningful regions in which different features are held.

It means to split the subject into pieces, or segments, that can be identified based on some parameters.

In computer vision, the process of partitioning an image into multiple zones, areas, or segments, according to their content.

In computer vision, a process by which an image is subdivided into regions having homogeneous visual features.

Grouping users according to a speculated buying propensity for services or products.

It is a process of partitioning a digital image into multiple segments to simplify the representation of image into meaningful and easier for analysis.

The process of classification of the area regarding a specific spot on the array to permit the distinction of the spot pixels either as foreground, or background.

An activity that subgroups individuals or objects in a particular domain into segments (clusters) that share a similarity or pattern.

The process of dividing the addressable market into smaller clusters by a marketing firm for clearly targeted marketing strategies.

Segmentation is partitioning an image into different parts according to their features and properties.

Grouping individuals according to the similar properties.

A subdivision of a population into segments with similar characteristics, such as age, education, income.

In image segmentation, the users select only that area of image that is of their interest. In this process the image is divided into multiple sections or structures of the interest, so that each section has characteristic similarity.

Process of identifying subgroups of people with similar behavioral or attitudinal patterns.

Segmentation refers to the automatic process of partitioning a data stream into multiple segments by set of predefined features (e.g. temperature, electricity consumptions, workdays, etc.).

The aim of image segmentation is the partition of the image in homogeneous regions. Segmentation refers to the process of partitioning a digital image into multiple segments (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image (see edge detection). Each of the pixels in a region are similar with respect to some characteristic or computed property, such as color, intensity, or texture. Adjacent regions are significantly different with respect to the same characteristic(s). Appendix A shows the bone segmentation of the image.

The process of building regions within an image which better represent the real world objects present in the image.

In computer vision, segmentation refers to the process of partitioning a digital image into multiple regions. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (structures) in images, in this case, the coronary tree in digital angiography frames.

Segmentation refers to the identification of groups of individuals that share some characteristic with each other but are different from the others. In marketing, those groups are defined as market segments and are further used for targeting and positioning.

An iterative process that leads to the foundation of similar groups according to a response variable

Segmentation refers to the automatic process of partitioning a data stream into multiple segments by set of predefined features (e.g. temperature, electricity consumptions, workdays, etc.).

It is the process of dividing the data in homogeneous groups so that similar data group together based on the chosen parameters so that it can be use more efficiently for marketing and operations purposes.

The process of identifying distinct groups of buyers who might require separate products and/or marketing mixes, then creating a profile of each group. Divide the total market of a product or service in a number of homogeneous subsets such as the habits, needs and tastes of its components, calling up each of these subsets as a market segment.

Another major group that comprises the world of data mining involving technology that identifies not only statistically significant relationships between explanatory and target variables, but determines noteworthy segments within variable categories that illustrate prevalent impacts on the target variable.

Another major group that comprises the world of data mining involving technology that identifies not only statistically significant relationships between explanatory and target variables, but determines noteworthy segments within variable categories that illustrate prevalent impacts on the target variable.

It is the process of dividing into separate parts or sections.

Data mining task in which the goal is to build a model that separates data into interesting and meaningful subgroups where all members of a subgroup share common characteristics.

Segmentation means audio segmentation which is partitioning an audio stream into its homogeneous units. It refers to partition respiratory sound stream into individual inspiratory and expiratory phases.

Partitioning of a digital image I into multiple non-overlapping regions such that the union of any two adjacent regions is not homogenous is called Image Segmentation.

It is the process of isolating some object level pattern within an image from the rest of the image portion. In case of character segmentation it is the process of isolating the characters from the background.

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, spending habits, and so on.

Text segmentation is the process of segmenting a text stream into topically coherent segments.

The partitioning of digital images into different regions, which group elements (pixels or voxels) with similar feature values.

It is the process of partitioning a digital image into multiple segments and makes it more understandable.

Image processing technique for distinguishing the different homogeneous regions in an image.

A process that partitions a digital image into disjoint (non-overlapping) regions, using a set of features or characteristics. The output of the segmentation step is usually a set of classified elements, such as tissue regions or tissue edges.

Segmentation is the process of stratifying the portfolio (product, market, channel etc.) into clusters based on attributes like risk, margins, criticality, revenue, volume, lead times, life cycle stage, etc., which helps the organization put more emphasis and resources on key customers and products and make decisions on product portfolio management, as well as entry/exit of markets to enable an organization to offer differentiated service treatment to certain groups.