Last updated on July 28, 2019
What is Digital Image processing? When processing a digital image by means of a digital computer is called digital image processing. In order to get an enhanced image, we use computer algorithms in digital image processing.
Image processing include the following steps:
- Importing the image via image acquisition tools
- Analysing and manipulating the image
- Output in which result can be altered image or a report which is based on analyzing that image
Phases of Digital Image Processing
In order to get an enhanced image we use Image processing, which is a technique to perform operations on an image. We can relate it to signal automation in which input is an image and output may be an image or characteristics or features associated with that image. Nowadays, image processing is advancing day by day. It is a core research area within engineering and computer science disciplines.
PHASES OF IMAGE PROCESSING:
- IMAGE ENHANCEMENT
- IMAGE RESTORATION
- COLOR IMAGE PROCESSING
- WAVELETS AND MULTI-RESOLUTION PROCESSING
- IMAGE COMPRESSION
- MORPHOLOGICAL PROCESSING
- SEGMENTATION PROCEDURE
- REPRESENTATION & DESCRIPTION
- OBJECT DETECTION AND RECOGNITION
For image processing we use two types of methods analogue and digital image processing. For the hard copies like printouts and photographs we use Analogue image processing. While using these techniques, Image analysts use various fundamentals of interpretation. Computers help Digital image processing in manipulation of the digital images. The three general phases while using digital image processing technique are pre-processing, enhancement, and display, information extraction.
Interaction of objects
A Human-Computer Interaction program will be achieved which will display images through Image Processing and Pattern Recognition. This program will bring you a new experience because of the new and unique camera-based capture of non-contact input mode. At the same time, it is also an experimental method which can separate objects from images and more complete detection of object motion by a collection of various images processing algorithms. What’s more, this system is designed as a prototype of exhibition items and will help the future development of the items become more maturity, more variation.
Syntactic and semantic approach in Image processing
Syntactic and Semantic approaches are important in image processing. The methodology involves the injection of semantic considerations. The semantic factors that should be kept under consideration include feature vectors, selection restrictions, feature transfer functions, semantic well-formedness, etc. We extract a description scheme which carries the numerical, the structural, and the prior real-world information about the pattern we want to extract through such injections. From the description we can construct an analytical mechanism, the creation machine, which will find the desired pattern amide chaos of noisy primitives.
Goal of Computer Vision
Computer vision is basically a subfield of artificial intelligence and the main purpose of computer vision is to program a computer to “understand” a scene or features in an image.
Typical goals of computer vision include:
- The segmentation, location, and recognition of certain objects in images (e.g., human faces)
- The evaluation of results (e.g., segmentation, registration)
- Registration of different views of object
- Tracking an object through an image sequence
- Mapping a scene to a 3D model of the scene
- Estimation of the 3D pose of humans and their limbs
- Content-based image retrieval
These goals are achieved by means of statistical learning, pattern recognition, projective geometry, image processing, graph theory and other fields.