EMERGING TRENDS AND TECHNIQUES IN COMPUTER GRAPHIC DIGITAL IMAGE PROCESSING


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Digital image processing is the method of studying, analyzing and enhancement of images using computers to extract some useful information from the image. It involves the importation of an image where signals for processing and computer graphics are used when output is processed in either image form or a report form. Image processing is a growing technology that is used in various fields of research such as computer science and engineering. In years' image processing has been improving with the latest trends including pattern recognition, restoration and enhancement, efficient coding and 3D image processing. Some of the trends in graphical image processing in various fields include:

a) OPTICAL FLOW
Optical flow is the pattern of motion and edges in a visual scene of images, objects, and surfaces caused by relative motion between an observer and the scene. Numerical calculations and algorithms are used to calculate the image time and vector field to approximate the gradient of the image. In graphical image processing, optic flow is used in motion estimation, object tracking and machine vision. The technique involves motion estimation determined by the movement from one image to another. The calculations are then used to process the image to enable the understanding and the analysis of an image based on the motion which is not evident to the naked eyes.

b) PATTERN RECOGNITION
Pattern recognition is a technique used to detect and classify an image based on the key features used in a certain image. It involves processes used to extract, classify and describe the patterns found in a certain image using either 2 Dimension,3 Dimension or even 1 Dimension. The technique also uses various mathematical methods to solve pattern recognition on various images.

c) STEREO VISION
Stereo vision is the extracting of 3 Dimensional information taken by two cameras displayed horizontally to obtain two different views of the same scene. The technique is used for computing depth information from the images captured by two or more cameras and observe a scene from two or more viewpoints and refer the position, structure, and relation to the objects in the scene. The exploitation of two different views done by the process of visual perception is used to achieve depth perception. The method has been used in graphical image design to make an analysis from images by getting two different views then compiling them to come up with a conclusion.

d) FEATURE EXTRACTION
Feature extraction technique involves extraction and selection of effective features from images to solve an existing problem and find a solution. It involves the reduction of attributes from an image which has some significance then analyzing them to come up with a solution about the image. Feature extraction gives the ability to interact and access different information from a given image then process the information to come up with a reasonable conclusion.

e) EDGE DETECTION
Edge detection is a graphical image processing technique and segmentation that involves analyzing the boundaries of images where the brightness of an image changes sharply. It is mainly used when segmenting an image since the edge is a basic feature of the image and it makes it easier for humans to understand. Algorithms that focuses on the edge through segmentation are used to analyze the image and give a detailed analysis of the image.

f) IMAGE REGISTRATION.
Image registration is a graphical image technique that involves aligning two or more images from a given scene or also aligning multiple scenes to form one image. The technique is mainly used in the medical field where surgery that involves guided images are performed such as the brain where a neurosurgeon is able to locate the size and location of a particular tumor. Some features are extracted from a different cluster of an image obtained from clustering algorithms.

g) AFFINE TRANSFORMATION
The affine transformation is a graphical image processing technique that involves correcting geometric distortions and deformations in an image and also preserving points, straight lines, and planes. It makes it easier to process a given image if all features of the image are preserved hence giving thorough and detailed information of the image without leaving any information behind. Also, images that may have been damaged are also able to be restored through this technique.

h) COLOR IMAGE PROCESSING
Color image processing is a technique that involves the analysis of colors in an image. Color models are used such that each point in the image is represented by one color. Color is used in a description that makes identification of an image extracted from a scene easily. It is not an efficient way of image processing especially if algorithms are used in the same since colors such as red, green, and blue contain components that highly correlate. Color sensors and hardware for processing color images have been developed to be able to use color to analyze an image.

i) IMAGE SEGMENTATION
Image segmentation is a graphical image processing technique that decomposes an image into segments by grouping them into segments with similar characteristics eg similar pixels. A computer vision application is used to perform this procedure with a segmentation algorithm with the knowledge or strategies that allows effective segmentation. The analysis of each segment gives the general view and information contained in the image.
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