By Debahuti Mishra, Shruti Mishra (auth.), Srikanta Patnaik, Yeon-Mo Yang (eds.)
This particular Edited quantity is a distinct strategy in the direction of Computational answer for the approaching box of research known as imaginative and prescient technological know-how. From a systematic firmament Optics, Ophthalmology, and Optical technological know-how has passed an Odyssey of optimizing configurations of Optical structures, Surveillance Cameras and different Nano optical units with the metaphor of Nano technological know-how and know-how. nonetheless those structures are falling wanting its computational element to accomplish the top of human imaginative and prescient approach. during this edited quantity a lot consciousness has been given to handle the coupling matters Computational technology and imaginative and prescient experiences. it's a finished number of learn works addressing a number of similar parts of imaginative and prescient technology like visible conception and visible process, Cognitive Psychology, Neuroscience, Psychophysics and Ophthalmology, linguistic relativity, colour imaginative and prescient and so on. This factor consists of a few most modern advancements within the kind of study articles and displays. the amount is wealthy of contents with technical instruments for handy experimentation in imaginative and prescient technological know-how. There are 18 learn papers having importance in an array of software components. the amount claims to be a good compendium of computing advancements like common development Mining, Genetic set of rules, Gabor clear out, help Vector laptop, zone established masks clear out, 4D stereo digital camera platforms, critical part research and so forth. The particular research of the papers can immensely gain to the researchers of this area. it may be an Endeavour within the pursuit of including worth within the latest inventory of information in imaginative and prescient technological know-how.
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The proposed method is robust and independent of style of hand writing. In future, we extend the proposed method for the remaining Indian scripts and also for script type identification at word level. Furthermore, the methods proposed for script type identification from tri-script documents can be improved to increase the recognition accuracy. Acknowledgment. We are very grateful to Dr. S. Hiremath, Professor, Department of Computer Science, Gulbarga University, Gulbarga and Dr. Peeta Basa Pati, Bangalore, for their valuable suggestions during this work.
In this paper, a multiple feature based approach is presented to identify the script type of the collection of handwritten documents. Eight popular Indian scripts are considered here. Features are extracted using Gabor filters, Discrete Cosine Transform, and Wavelets of Daubechies family. Experiments are performed to test the recognition accuracy of the proposed system at line level for bilingual scripts and later extended to trilingual scripts. We have obtained 100% recognition accuracy for bi-scripts at line level.
Anita Algorithm-3 (Gabor combined with wavelets) Input: Image in gray scale at line level. Output: Feature vector Method: 1. Perform steps 1 through 7 of algorithm-1 to obtain the convolved images(total 18). 2. Perform Wavelet (Daubechies 9) decomposition for the convolved input images (total 18) to obtain approximation coefficients (cA), vertical coefficients (cV), horizontal coefficients (cH), and diagonal coefficients (cD). Compute the Standard Deviation for each frequency band separately for all images.