One can define Image Processing as a means of converting an image into its digital form and perform some operations using computer algorithms to get an enhanced image or to extract useful information from it.
Image processing helps to identify what’s present in an image and used in the development of most of the Computer Vision applications. It is one of the rapidly growing technologies with an increasing number of applications in various fields.
Applications of Image Processing
Below is a list of major fields in which Image Processing is widely used:
Image Sharpening and Annotation
Image sharpening and annotation refers to the process of enhancing an image to achieve the desired output and includes sharpening, blurring, zooming, detecting of edges, recognition, and retrieval of images.
In the medical field, Image Processing has various applications from UV and X-Ray imaging to the gamma-ray image, PET Scan, and medical CT. Image Processing techniques help to improve the diagnosis of heart diseases, identify lung disease using X-Rays and detect breast tumors.
Image processing techniques are applied to process the images of the earth’s surface captured by the remote sensing satellites. It helps to detect infrastructural damages caused due to an earthquake, analyze the situation for flood control, monitor agricultural production, interpreting objects and areas for city planning and in resource mobilization.
Training the robots to see and identify the objects and hurdles. Robots can be trained on hurdle detection by helping them to identify various objects in an image and calculate the distance between them and the hurdles. Image Processing can also be used to train a line follower robot to move in a specific path and perform tasks.
Image Processing helps to process, analyze and present microscopic images and enhances the ability of the scientists and researcher in understanding the microscopic world.
Image Processing helps to improve the quality of the videos and can be used for performing various tasks such as noise reduction, motion detection, detail enhancement, rate conversion, and color space conversion.
Pattern Recognition involves the combination of Image Processing and machine learning to identify objects in an image and train the system to identify the pattern changes. It is mainly used in the recognition of images, computer-aided diagnosis and handwriting recognition.