Active contours are defined models for segmentation of pixels from the required region of interest for which processing is performed to obtain the outcome for research. Active contour technique is applied for separation of foreground from the background and the segmented region of interest undergoes further image analysis. These models are considered because they help in segmentation of the target object of particular data or information values from an image. In this chapter, we discuss about an image segmentation technique called active contour models. Segmentation can also be performed with the help of feature extraction process from the pixels of the image. Thresholding, region growing, region splitting, region merging, detection of boundary discontinuities (point, line and edge detection), watershed segmentation and active contours are few examples of image segmentation process. Image segmentation can be classified into different types of algorithm based on the discontinuity and similarity of intensity values. With the process of segmentation, desired output from the pixels of interest is obtained. Image segmentation is described as the fundamental process in many computer vision and medical image analysis applications. Different modality of images can be processed and segmented for separating the necessary pixel information. Medical image analysis requires segmentation of images for processing of the region of interest. Region of interest should be simple, uniform and homogenous with smooth boundary Image analysis defines certain objectives for segmentation process:ĭecompose the image into parts for future analysis Image segmentation provides definite and useful information or data for the high standards of automatic image analysis.
If image segmentation is performed effective, the after stages of image analysis are made easier. In medical image analysis, segmentation is very much necessary where region of study or research is defined to a particular section of the image. Segmentation is a crucial process in Image analysis because it paves path for future processing of images. The process of segmentation does not provide information about the entire image rather associates pixel data of only the region of interest. Region of interest possesses a group of pixels defined with a boundary and these may contribute to different forms such as circle, ellipse, polygon or irregular shapes. The main aim of image segmentation is to segment the meaningful regions of interest for processing. Image segmentation can be defined as the segregation of pixels of interest for effective processing. Segmentation is the process of separation of required information from a data for further processing. Segmentation is a part of image processing used for segregation of regions. The images can be defined in different dimensions which can be used for processing. Processing of images is carried out by avoiding certain features like noise and signal distortion that affects the information present in the images. Image processing makes use of a wide range of techniques to process the input information which is available in the form of an image. Image processing can be defined as computerised processing of images of different types to obtain the desired output. *Address all correspondence to: Introduction Department of Biomedical Engineering, Vels Institute of Science, Technology and Advanced Studies (Deemed to be University), Chennai, India.Thus, the active contour segmentation is used for the separation of pixels of interest for different image processing.
Active contours can also be used in motion tracking and stereo tracking. In medical imaging, active contours are used in segmentation of regions from different medical images such as brain CT images, MRI images of different organs, cardiac images and different images of regions in the human body. Active contour models are used in various image processing applications specifically in medical image processing. The contour depends on various constraints based on which they are classified into different types such as gradient vector flow, balloon and geometric models.
Active contour defines a separate boundary or curvature for the regions of target object for segmentation. Active contour is one of the active models in segmentation techniques, which makes use of the energy constraints and forces in the image for separation of region of interest. There are different techniques used for segmentation of pixels of interest from the image. Segmentation is a section of image processing for the separation or segregation of information from the required target region of the image. Image processing is a technique which is used to derive information from the images.
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