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Advance Teaching pedagogy is one of the innovative approaches to enhance teaching learning process. Due to the development of new technologies and development of many globalization, teaching learning process plays a vital role among students where the education has been expanded to macro level. Hybrid teaching includes e learning in addition to the face to face teaching. In this paper, various innovative learning strategies for modern technology are discussed in details. Use of smart gadgets for different tasks like teaching, designing question papers, assessment of student, feedback and research methodology are discussed.

Segmentation separates an image into different sections badsed on the desire of the user. Segmentation will be carried out in an image, until the region of interest (ROI) of an object is extracted. Segmentation reliability predicts the progress of the various segmentation techniques. In this paper, various segmentation methods are proposed and quality of segmentation is verified by using quality metrics like Mean Squared Error (MSE),Signal to Noise Ratio (SNR), Peak- Signal to Noise Ratio (PSNR), Edge Preservation Index (EPI) and Structural Similarity Index Metric (SSIM).

Objectives: To develop presents an efficient algorithm for binarization of text from videos. However, it is a challenging and difficult task in image processing, due to their complicated background and non uniform character size. Method/Analysis: This study focuses a novel approach for binarization of text region from videos based on Hill climbing Algorithm. Symmetric filtering and graph cut algorithms are used to refine the obtained clusters. Finally, an optimal clustering selection algorithm is applied to obtain the text region. Findings: The experimental results show that the proposed text binarization technique is robust in text detection with various character size and complicated background. Data sets are taken from the You Tube Video Text (YVT) harvested from YouTube. Application: This proposed binarization technique is applicable to automated licence plate recognition system, especially to identify Indian vehicles licence plates.