The existing location anonymity algorithms do not consider the distribution of user density in the region. The area of anonymous domain is not the most appropriate and the query workload is redundant. To solve this problem, this paper proposes optimal anonymous location privacy protection algorithm based on grid user density. Taking the user density of the regional grid as the core and using reasonable

Sign language is a medium of communication for people with hearing disabilities. Static and dynamic gestures are identified in a video-based sign language recognition and translated them into humanly understandable phrases to achieve the communication objective. However, videos contain redundant Key-frames which require additional processing. Number of such Key-frames can be reduced. The selection

An architecture for automatic lung tissue classification method based on the Deep Learning techniques is designed in this paper. Recent works on Deep Learning techniques achieved impressive results in the field of medical image classification. So, we designed a Convolution Neural Network (CNN) for the classification of five categories of Interstitial Lung Diseases (ILD) patterns in High-Resolution

Motion estimation (ME) being a fundamental process of crowd behavior analysis experienced real challenges at high densities due to visual ambiguities and occlusion problems etc. Various surveys reported in the past years summarize conventional ME methods for crowd behaviors at low/medium densities. In this paper, we focus on state-of-the-art fluid dynamics (FD) ME methods developed over the last one

Image super-resolution (SR) techniques aim to estimate high-resolution (HR) image from low-resolution (LR) image. Existing SR method has slow convergence and recovery of high-frequency details are inaccurate. To overcome these issues, two algorithms have been proposed for image SR based on non-local means improved iterative back projection (NLM-IIBP), deep convolutional neural network improved iterative

In recent times, the applications of multimedia are rising in a greedy mode and hence the amount of video transactions is also increasing exponentially. This has shouted great demands on effective models on video encoding and also for reducing the transmission channel congestion. This research work introduces a managing technique termed weighted encoding for High-Efficiency Video Coding (HEVC). HEVC

Watermarking provides an efficient mechanism for copyright protection of digital media by embedding information in the object to identify the owner. This paper proposed a watermarking technique that can successfully embed a grey-scale image in a 3D mesh object. In our proposed technique, each three vertices of the 3D object can hide one pixel from the secret image. The experimental results showed that

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features

Face Recognition is the process of identifying and verifying the faces. Face recognition has vast importance in the field of Security, Healthcare, Banking, Criminal Identification, Payment, and Advertising. In this paper, we have reviewed various techniques and challenges for the face recognition. Illumination, pose variation, facial expressions, occlusions, aging, etc. are the key challenges to the

Surface Fourier transform profilometry (FTP) is a technique used for reconstructing three-dimensional (3-D) surface topography using light. It has been widely used in machine vision for biomedical and biometric automations, providing solutions beyond conventional 2-D imaging. This paper proposes an implementation of the handheld pocket-size FTP for 3-D surface profile imaging using a projector-enabled