Application of DSP
- 1. DIGITAL SIGNAL PROCESSING Submitted to: Dr. Maheshwar R Submitted by: KUNAL RANA 18BEE10024
- 2. Digital Signal Processing: ● Signals can be defined as something that conveys information. They are of two types: a) Analog signal b) Digital signal ● Signal processing refers to Analyzing, modifying and synthesizing the signals of get a desired output. ● Analog signal can be converted into digital signals by sampling or quantization. ● Analog signal is converted into discrete signal and then it is converted into digital signal. ● Digital signal processing refers to analyzing these digital signals to get the desired outputs.
- 3. Image Processing: 1. Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. 2. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. 3. Image processing basically includes the following three steps: ● Importing the image via image acquisition tools; ● Analysing and manipulating the image; ● Output in which result can be altered image or report that is based on image analysis.
- 4. Digital Image Processing: ● Digital image processing techniques help in manipulation of the digital images by using computers. The three general phases while using digital technique are pre-processing, enhancement, and display than Information is extracted. ● Digital Images are 2D signals that consist of picture elements called pixels. Each pixel can be represented as x(m,n), where m is the row (height) , n is the column (width). ● Images can be of greyscale or colour type and we use DSP to split multidimensional signals and extract each component. Concepts of linearity,convolution,fourier transform,interpolation and sampling are used to achieve this. ● However new manipulations and specialized signals are generated to overcome limitations.
- 5. Image Processing Techniques: • Image representation : Cartesian, support and image representation of 2D signals called pixels. • Image preprocessing : By Scaling, i.e, magnification of image to have a closer view by magnifying or zooming the interested part in the imagery. By reduction, bringing the unmanageable size of data to a manageable limit. For resampling an image. • Image enhancement : To accentuate certain image features for subsequent analysis or for image display. • Image analysis : Making quantitative measurements from an image to produce a description of it • Image segmentation:The process that subdivides an image into its constituent parts or objects.
- 6. Advantages of DIP: ● Image processing improves edge recognition, and when combined with sub-pixel processing, reliable measurement is consistently achieved. ● Higher speed ● Available in any desired format . ● Accuracy of measurement is even maintained when monitoring curved, reflective surfaces where subtle changes in colour. ● Images can be stored in the computer memory and easily retrieved on the same computer screen.
- 7. Disadvantages of DIP: ● One of the principle disadvantages of conventional binary processing, or grayscale processing as it’s often known, has been the inability of products to recognise contrast effectively. ● The initial cost can be high depending on system used . ● Once the system is damaged , images will be lost.
- 8. ● In Agricultural Landscape: Irrigation monitoring and providing information can be made possible by tracking satellite imaging of the fields.Quality of yields can be ensured by the reliable and accurate method of image processing through sorting and grading of fresh products. APPLICATIONS OF DIP: Image processing technology extracts information from images and integrates it for a wide range of applications. ● In Production Automation: Image processing applications can make it possible for machines to act as more self-sufficient and ensure the quality of products :- :-
- 9. ● Disaster Management:Drone aircrafts monitoring environmental and traffic conditions can use image processing to capture high resolution real-time videos and photographs. monitoring the progress and ensuring co-ordination during such rescue operations can be made easier with real-time image processing techniques. ● Biomedical and Other Healthcare Applications: 3D imaging and rendering, doctors can see extremely high quality 3D images of organs that they couldn’t have seen otherwise. This, in turn, can help them carry out delicate surgeries and make accurate diagnoses.
- 10. THANK YOU.