Motilal Nehru National Institute of Technology Allahabad

About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.

Effect of nanoalumina in epoxy adhesive on lap shear strength and fracture toughness of aluminium joints

Abstract: Lap shear strength and opening mode fracture toughness of epoxy/alumina nanocomposite adhesives in bonded aluminium alloy joints were determined using a single lap joint, and double cantilever beam...

De-noising of ultrasound image using Bayesian approached heavy-tailed Cauchy distribution

Abstract: Medical ultrasound images are used in clinical diagnosis and generally degraded by speckle noise. This makes difficulty in automatic interpretation of diseases in ultrasound images. This paper presents a speckle removal algorithm by modeling the wavelet coefficients. A Bayesian approach is implemented to find the noise free coefficients. Cauchy prior and Gaussian Probability Density Function (PDF) are used to model the true wavelet coefficients and noisy coefficients respectively. A Maximum a Posteriori (MAP) estimator is used to estimate the noise free wavelet coefficients. A Median Absolute Deviation (MAD) estimator is used to find the variance of affected wavelet coefficients in finest scale. The proposed method is compared with existing denoising methods. The experimental results show that the method offer up to 21.48% enhancement in Peak Signal to Noise Ratio (PSNR), 1.82% enhancement in Structural Similarity Index (SSIM), 1% enhancement in Correlation coefficient (ρ) and 7.68% enhancement in Edge Preserving Index (EPI) than best existing wavelet modeling method. The results indicate that the proposed method outperforms over existing methods, both in noise reduction and edge preservation.

Building extraction from very high resolution multispectral images using NDVI based segmentation and morphological operators

Abstract: In this paper, we have proposed an approach for building extraction from very high resolution (VHR) multispectral images using NDVI (Normalized Difference Vegetation Index) based segmentation and morphological operations. This approach uses both spatial and spectral properties of an image scene for building detection. Spectral properties are related to NDVI based segmentation and spatial properties are related to the morphological operations. Normally an image scene consists of natural region (vegetation and soil) and manmade regions (buildings and roads). Use of NDVI (spectral properties) eliminates the chance of shadow being a building region and other similar regions that are not road like soil, vegetation etc because shadow is a spatial property and NDVI is based on spectral property irrespective of brightness in the image. By using NDVI we can eliminate the natural regions from the manmade regions because NDVI values of these two regions differ a lot, so using NDVI as a threshold we can segment image into two parts one is natural and other is our desired parts that consists of manmade regions (buildings and roads). After segmentation here comes the use of spatial property, use of morphological operation to separate the roads from building regions on the basis of their spatial property that roads have elongated and larger area than buildings and mostly building has the rectangular rooftops. This approach provides very satisfactory results with very less overhead and time.