Abstract

This paper is based on Medical image sequence compression. In this paper, the author has compared two lossless compression techniques, viz. Set Partitioning in Hierarchical Tree (SPIHT) and Spatial Orientation Tree Wavelet (STW) with Block matching algorithms, Diamond Search (DS) and Adaptive Rood Pattern Search (ARPS). Every day large amount of medical videos are created by pathology labs and image diagnostic centers and in order to store these videos, large amount of memory space is required. To reduce this memory space, he has performed compression, in such a way that the picture quality of the video is maintained. This paper is based on comparisons between SPIHT+DS and STW+ARPS. Both techniques are compared in terms of Compression ratio, Peak Signal to Noise Ratio, and Time. The STW+ARPS gave better result compared to SPIHT+DS. STW+ARPS executed the whole process within 193 seconds. ARPS is the fastest Block matching algorithm with a better picture quality.

Abstract

The advancement in sophisticated technology led to the development of sensors that are helping humans in each and every walk of their life. With the availability of surface mount technology techniques in semiconductor manufacturing systems, many miniaturized devices are currently being produced that are used in sensing parameters like temperature, pressure, level, flow, velocity, thickness, etc. They are designed in such a way that they can even withstand harsh environments and cryogenic conditions with an added advantage of being passive in nature. These devices can be applied to versatile industries, but whereas in medical segment, their significance of impact is more due to wide variety of challenges yet to be answered by conventionally available sensing techniques. As wireless techniques involve signal distortion, transmission problems, and data losses, currently available micro sensors are up to the benchmark, that are able to meet the industry standards by overcoming the general issues in wave propagation.

This paper is a mainly focused medical domain on scanning with MEMS based devices. As imaging of internal body parts in human is most important task involved in medical domain as it helps to identify damaged area, amount of infection, breakage in bones, clots in blood, disease monitoring, clinical diagnostics, etc. Here, a micromirror is used that moves thousands of times per second to generate an invisible grid and that is finally analysed in 3D for imaging. In this model, the dynamic vibrating behaviour of the solid mirror is analysed with air surrounding it using shell elements. The model is solved both for frequency-domain sweep and Eigen frequency study using COMSOL Multiphysics software. The displacement (or velocity) is evaluated at the tip of the mirror for the frequency sweep. This paper focuses on simulation and analysis of micromirror and its corresponding displacement response in terms of torquing force. Current challenges and future scope of micro-electro-mechanical-systems based wireless Micromirror imaging sensor for different medical applications are discussed. This sensor is used for various scanning, fibre optics microscopy applications, and in 3D tissue analysis and for various optical engineering applications.

Abstract

Adjacency or neighbourhood plays a vital role while removing noise in many key areas of image processing. This is in view of the fact that once noise corrupts an image, there can be a deviation from original intensity distribution. A location where noise has its impact will clearly have a value which differs from surroundings. The presence of this noise due to various means will definitely affect the accuracy of many computer vision related applications, which is very much critical in medical related applications. In the current work, an algorithm is developed which can handle multiple types of noise with minimum degradation. Unlike conventional filters which directly operate on pixel values, the algorithm concentrates on minimizing the differences between pixels in the process of noise reduction. Peak Signal to Noise Ratio (PSNR) is used as a performance metric for verifying the efficiency of the algorithm.

Abstract

The objective is to estimate change in water level of lakes using satellite images. High resolution images provided by Landsat satellites are collected and passed through an image processing stage for calculating the lake properties such as Area and Perimeter. The images used in this paper are obtained from the USGS website. All the selected images are cloud free. In this paper, changes in water level are observed by calculating the areas and perimeters of four different lakes in two different times, using satellite images. These satellite images were acquired by Thematic Mapper on the Landsat5 and the Operational Land Imager (OLI) on Landsat 8. To detect the changes, image is classified into two classes, namely land and water. Thus, lake surface and surrounding ground were precisely separated. Then Perimeter (boundary) and Area of the lake are calculated. Area is computed by enumerating black colored pixels and Perimeter by enumerating edges of the lake, i.e. image gradient vector, gives the perimeter of the lake. The Area and Perimeter of the lake change as the water level changes.

Abstract

Nowadays, the idea of transmitting the text or data safely and securely is the most crucial part. Hiding capacity of the data and its confidentiality plays a vital role in covert communication. A solution for this challenging part of the secure transmission is presented in this paper, wherein the security of transmission is ensured, by first encrypting the data that is to be transmitted by using the RSA algorithm, so the part of security and confidentiality of the message is covered and then Image Steganography is used. It is a technique where the transmitting data is hidden in an image. For hiding the information in an image there are many steganography techniques, in which LSB technique is chosen in this case. In this technique, the data is the text message which is converted into binary format by considering its ASCII values and then the bits of the information is hidden in the least significant bits of the R, G, B values of the pixels of the image.

Abstract

Most of the embedded products designed today are Vision-based systems with camera as a main component for its implementation. The cameras with wide angle lens enable them to capture images giving high-level descriptions of the scene useful for several applications, such as video surveillance, motion analysis, human/object detection, etc. However, images obtained using these wide angle lenses tend to be distorted causing straight lines from the scene to appear as curves in the image plane termed to be as Barrel or Radial Lens Distortion. Such distortion produces less realistic images and affects objects relative sizes, depending on their position in the image. It may be still acceptable in fisheye images, but in fisheye videos, the resulting distortion renders them hard to understand and uncomfortable to watch. It is therefore desirable to correct the barrel distorted images/video before presenting to the end viewer. A lot of research on algorithm that corrects for the distortion of the lens has been done to resolve this problem of radial distortion. Implementing this correction algorithm on a hardware platform can help in developing an ASIC that could be embedded into these Vision-based systems. In this paper, the authors review a framework to correct a wide angle lens distortion based on rectilinear and polynomial based model. The MATLAB implementation of these Distortion correction algorithms is done and comparison of their result is made. It is observed that rectilinear model gives efficient results as compared to polynomial based approach. The hardware platforms used to implement these algorithms are also been discussed. The analysis of these platforms suggest the advanced FPGAs (Field Programmable Gate Arrays) with embedded DSP blocks as a good choice for implementing these Barrel distortion correction algorithms for real time video capturing systems using wide angle lenses making it distortion free.