Tanima Dutta

A Continuous Hand Gestures Recognition Technique for Human-Machine Interaction Using Accelerometer and Gyroscope Sensors

Recent advances in smart devices have sustained them as a better alternative for the design of human-machine interaction (HMI), because they are equipped with accelerometer sensor, gyroscope sensor, and an advanced operating system. This paper presents a continuous hand gestures recognition technique that is capable of continuous recognition of hand gestures using three-axis accelerometer and gyroscope sensors in a smart device. To reduce the influence of unstableness of a hand making the gesture and compress the data, a gesture coding algorithm is developed. An automatic gesture spotting algorithm is developed to detect the start and end points of meaningful gesture segments. Finally, a gesture is recognized by comparing the gesture code with gesture database using dynamic time warping algorithm. In addition, a prototype system is developed to recognize the continuous hand gestures-based HMI. With the smartphone, the user is able to perform the predefined gestures and control smart appliances using the Samsung AllShare protocol.

Geographic Routing in Clustered Wireless Sensor Networks Among Obstacles

An important issue of research in wireless sensor networks (WSNs) is to dynamically organize the sensors into a wireless network and route the sensory data from sensors to a sink. Clustering in WSNs is an effective technique for prolonging the network lifetime. In most of the traditional routing in clustered WSNs assumes that there is no obstacle in a field of interest. Although it is not a realistic assumption, it eliminates the effects of obstacles in routing the sensory data. In this paper, we first propose a clustering technique in WSNs named energy-efficient homogeneous clustering that periodically selects the cluster heads according to a hybrid of their residual energy and a secondary parameter, such as the utility of the sensor to its neighbors. In this way, the selected cluster heads have equal number of neighbors and residual energy. We then present a route optimization technique in clustered WSNs among obstacles using Dijkstras shortest path algorithm. We demonstrate that our work reduces the average hop count, packet delay, and energy-consumption of WSNs.

A robust compressed domain video watermarking in P-frames with controlled bit rate increase

In recent years video watermarking has become an important research issue due to increase in threats of video piracy, content authentication, and ownership integrity. In this paper, we propose a robust watermarking method with the blind extraction process for compressed video streams like H.264/AVC. The method embeds invisible watermark bits into the P-frames. Appropriate block selection and the embedding algorithm restrict the increase in video bit rate. The security of the method lies in selecting candidate blocks using a pseudo random key from set of previously selected blocks. The simulation results show that the proposed method is robust against common image and video watermarking attacks. A robust watermark is generated in order to withstand frame drop and insert attacks, which increases the overall robustness of the proposed method.

A robust watermarking framework for High Efficiency Video Coding (HEVC) - Encoded video with blind extraction process

We propose a robust watermarking framework with a blind extraction process for HEVC encoded video, where a readable watermark is embedded invisibly in intra predicted blocks of the HEVC encoded video.Our watermarking framework enforces security by exploring the spatio-temporal characteristics of the compressed video and a random key for selection of embedding regions.We also analyze the strengths of different compressed domain features of HEVC encoded video for implementing the embedding algorithm.Experimental results demonstrate that the proposed work restrict the increase in video bit rate and degradation of perceptual quality.The proposed framework can also survive filtering, compressions, and noise additions maintaining good quality and robustness. Digital watermarking is an efficient and promising means for copyright protection of multimedia objects. Digital videos are stored and transmitted in a compressed format, which has drawn a great deal of attention in compressed domain watermarking for video. The embedding and extraction of watermark bits in compressed domain, therefore does not require complete decoding and re-encoding of the compressed video. There have been several compression standards for video. High Efficiency Video Coding (HEVC), a successor to H.264 Advanced Video Coding (AVC), is the latest standard for video compression with high compression efficiency. In this paper, we propose a robust watermarking framework with a blind extraction process for HEVC encoded video. A readable watermark is embedded invisibly in 4 × 4 intra predicted blocks of the HEVC encoded video. Our watermarking framework enforces security by exploring the spatio-temporal characteristics of the compressed video and a random key for selection of embedding regions. We also analyze the strengths of different compressed domain features of HEVC encoded video for implementing the embedding algorithm. Experimental results demonstrate that the proposed work restrict the increase in video bit rate and degradation of perceptual quality. The proposed framework can also survive filtering, compressions, and noise additions maintaining good quality and robustness.

Object Extraction Using Novel Region Merging and Multidimensional Features

Understanding natural images is a difficult task. One method to accomplish that can be, first, segment the image into regions of similar characteristics and then apply some object extraction scheme. Alternatively, extraction of characteristics of the desired objects can be initiated at the beginning. In this paper, we propose a scheme that adopts the former approach. An image is first segmented and then a novel region processing algorithm is applied. It is found that the proposed algorithm is capable of removing a high percentage of insignificant regions. Following region processing, a multidimensional feature extraction scheme is used. A set of five primitive and non-primitive features are used to create the feature vectors. The image dataset is divided into two parts, i.e. training and test sets. Results show the effectiveness of the proposed feature vector in extracting known objects present in natural and specific domain images.

MCRD: Motion coherent region detection in H.264 compressed video

One of the challenging issues in video watermarking is robustness against collusion attacks. To resist collusion attack, the same video scene should carry the same watermark, whenever and wherever it appears in the video. Inter-frame correlation is more within a short video neighborhood when no scene change is detected. Motion coherency has recently been recognized as a desirable property for watermarks to resist temporal frame averaging attacks. To the best of our knowledge, motion coherent watermarking in compressed domain has not yet been well explored. In this paper, a compressed domain technique has been proposed to detect motion coherent regions within a short video neighborhood. The time complexity of the proposed method is discussed. Simulation results evaluate the effectiveness of the proposed method.

An Efficient Framework for Compressed Domain Watermarking in P Frames of High-Efficiency Video Coding (HEVC)--Encoded Video

Digital watermarking has received much attention in recent years as a promising solution to copyright protection. Video watermarking in compressed domain has gained importance since videos are stored and transmitted in a compressed format. This decreases the overhead to fully decode and re-encode the video for embedding and extraction of the watermark. High Efficiency Video Coding (HEVC/H.265) is the latest and most efficient video compression standard and a successor to H.264 Advanced Video Coding. In this article, we propose a robust watermarking framework for HEVC-encoded video using informed detector. A readable watermark is embedded invisibly in P frames for better perceptual quality. Our framework imposes security and robustness by selecting appropriate blocks using a random key and the spatio-temporal characteristics of the compressed video. A detail analysis of the strengths of different compressed domain features is performed for implementing the watermarking framework. We experimentally demonstrate the utility of the proposed work. The results show that the proposed work effectively limits the increase in video bitrate and degradation in perceptual quality. The proposed framework is robust against re-encoding and image processing attacks.

Motion compensated compressed domain watermarking

The security has become an important issue in multimedia applications. The embedding of watermark bits in compressed domain is less computationally expensive as full decoding and re-encoding is not required. The motion coherency is an essential property to resist temporal frame averaging based attacks. The design of motion compensated embedding method in compressed domain is a challenging task. As far we know, no such embedding method is explored yet. In this paper, we propose a motion compensated compressed domain embedding method within a short video neighborhood that gives acceptable visual quality, embedding capacity, and robustness. The simulation results show the effectiveness of the proposed method.

Least significant bit matching steganalysis based on feature analysis

Steganography is a science of hiding messages into multimedia documents. In steganography, there is a technique in which the least significant bit is modified to hide the secret message, known as the least significant bit (LSB) steganography. Several steganalyzers are developed to detect least significant bit (LSB) matching steganography. Least significant bit matching images are still not well detected, especially, at low embedding rate. In this paper, we have improved the least significant bit steganalyzers by analyzing and manipulating the features of some existing least significant bit matching steganalysis techniques. A comprehensive set of experiments is carried out to justify proposed methods applicability and evaluate its performance against the existing least significant bit matching steganalysis techniques.

Secure Network Steganographic Scheme Exploiting TCP Sequence Numbers

Network steganography is a relatively new area of research. Various network steganographic schemes that modifies the header of protocols like TCP and IP are present in literature. An observation suggests that packet length based schemes are suitable for transferring secret information across the network. This paper attempts to propose a novel steganographic scheme which uses the length of the TCP segments to transfer secret information. This scheme embeds the secret information in the TCP sequence number by adjusting the payload of TCP segments. Experiments and results show that this scheme is better than other existing schemes based on adjusting the length of packets.