Projects on DIP
The process of converting the information (or) delivering to a person as the easiest way is the diagrammatic representation of pictures. The words of thousands compensated by pictures. A man can convey an information using the image, because a man can easily understood the visual with the mental abilities. The easier way of getting an information from human is the pictorial representation.
Digital Image common building block is the pixel, the basic element of picture, factors depend on image resolution are
- Number of pixels per unit value.
- Total number of pixels
Image segmentation with projects on DIP Application:
- Regions of interest are detected by scene (or) Data annotation
- Exiting segmentation algorithm are categorized by data clustering ,edge – based segmentation, region – based segmentation.
Projects on DIP techniques for feature extraction:
- Stereo correspondence
- Region growing, Edge Detection.
- Tracing and corner feature Detection.
The process of stretch the contrasted images by the gray value redistribution called histogram equalization, which become more efficient by making threshold selection.
Classifiers are parallel piped classifier, Bayesian classifier, Minimum-Distance to mean classifier, Gaussian maximum likelihood classifier.
The method of creating a determination (or) converting the original Data termed as feature extraction. There is a problem of effective by the philosophical way and feature extraction efficient.
For the Demonstration of Accuracy classifact and finding the proposed algorithm choosing the appropriate features are done by testing the group of images.
The engineering find focus on the improvement and system evaluation that assist humans with recognizing patterns ability are the usually process of automatic pattern recognition.
The efficient approximation for classification and new images annotation are performed by algorithm estimation with variation methods.
The attempt of build system by scientific understanding to recognize patterns is the engineering method to pattern recognition.
The hierarchical description of fingerprint friction ridge are
Level 1: pattern
Level 2: minutiae points
Level 3: pores and ridge shape.
Digital camera composed of Dedicated Image processing chips. It has large application in the field of intelligent transportation systems.