• Bhargavi Patel
• Prof. Shilpa Serasiya

Digital image processing has become vital with the growing requirement of different devices to capture everything around the world. To recognize any object, its shape is extracted and matched with required object or dataset. Object recognition is all the objects are different in nature and they have different label. With this in mind, it has the different name and identity according to the description. My approach is to combination of stages of the digital image processing system, to identify a number in ancient languages like Sanskrit. Since the numbers are curved, there must be a specific process to recognize them. In this research, a new method for the classification of freeman chain code using four connectivity and eight connectivity events with deep learning approach is proposed. The existing Freeman Chain Code event data analysis techniques, sampled gray images of the existing events are not used, but image files of the three-phase Power Quality event data are analyzed by taking the advantage of the success of the deep learning approach (Convolution Neural Network) on image-file-classification. Therefore, the novelty of the proposed approach is that, image files of the voltage waveforms of the three phases of the power grid are classified. It is shown that the test data can be classified with 100% accuracy. The proposed work is believed to serve the needs of the future smart grid applications, which are fast and taking automatic counter measures against potential Power Quality event. My approach will prove relatively better results in terms of precision, accuracy and recall.

Freeman Chain Code, Digital Image Processing, Convolution Neural network, Ancient Numbers.

"SHAPE BASED RECOGNITION METHOD for NUMBERS USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.238-242, April-2019, Available :http://www.jetir.org/papers/JETIR1904034.pdf

"SHAPE BASED RECOGNITION METHOD for NUMBERS USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp238-242, April-2019, Available at : http://www.jetir.org/papers/JETIR1904034.pdf