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In the recent past, a medical 2D image fusion approach has played a vital role in the biomedical industry for diagnosing disease using various modalities of medical images. Biomedical 2D image fusion synthesis is a combining technique that merges useful information from two or more modalities of data captured through high definition scanning devices. The fused image is highly useful when doctors make emergency surgical decisions for their clinical patients. In this research, an innovative medical 2D image fusion approach called 2-Dimensional Double Density Wavelet Transform (2D-DDWT), based on maximization of scaling rule, is being proposed for the combination of CT and MRI images of human brain. The source image is applied to 2D-DDWT pursued by the fusion of sub images of coefficients based on high and low frequencies that are decomposed by transformation technique. The low frequency information is decomposed using the congruency rule of phase while the high frequency information is decomposed using 2D Gabor filter. The 2D-DDWT frequency coefficients are fused by using Principle Component Analysis (PCA) for the approximation parameters, and therefore the rule of selection maximum is being applied for the coefficients to improve features of image fusion such as segmentation. Maximization scaling rule is proposed for pixel level fusion to improve quality metrics. The quantitative and qualitative analysis proves the efficiency of the proposed methodology and demonstrates the improvement of the proposed methodology over existing methods.

Multimodal medical image fusion helps to acquire more information about both the functional and structural informations. More over storage problems can also be addressed properly when the fusion process is adopted. A hybrid image fusion is being sought for an optimum algorithm for a better quality image. This proposed work describes about the multimodal image fusion framework based on empirical mode decomposition of images and fusion by discrete wavelet transform method. The obtained fused image by the proposed method consists of all the functional information and also the spatial characteristics of original image. No distortion is also present in the fused image. In this proposed work Magnetic Resonance Imaging (MRI), and Computerized Tomography (CT) images of brain are used for fusion. The fusion results obtained by this method are observed and quantitatively analyzed. The hybrid fusion response of this approach depicts the dominance of the acquired results.

The clarity of the outdoor scene images very bad due to the environmental condition result in hazy image. The process of removing the fog from that image is called dehazing. The dehazing process is very difficult in the moving image or video image. The proposed method should improve this problem for the smooth driving of the vehicles by controlling the speed by comparing the image and the scene of video taken during driving. The proposed method should remove the haze so that it will increase the visibility of the image and multi scene. The proposed method can improve the colour changes in the image which is caused by airlight. The single frame is used for the enhancement of the foggy image remove the fog using the transmission map which contains multilevel. We make use of boundary constraints and global airlight estimation is taken into account. The method is fast and noise-free that generally arise in such enhancement techniques.

This paper addresses the train running autonomously without any human operators. Provides information to avoid train to train collisions, over speeding problem, signaling errors and unmanned railway crossing incidents. This afford a way for a passenger to know the train location, speed and direction in real time from anywhere in India through his mobile phone.CAN protocol interconnect all the train compartments with embedded network to ensure safety and security of passengers during disasters occurring within trains such as bomb blasts and fire outbreaks. This make obtainable way for a passenger to know the train location, speed and direction in real time from anywhere in India through his mobile phone. The CAN node is used to ensure the safety and comfort of the passengers. It also have audio speakers to inform the passengers about the approaching station and also to provide alert messages during a crisis situation.

Image fusion technique has been widely in use in many applications such as computer vision, surveillance, robotics, medical imaging, remote sensing etc. Medical image fusion plays a vital role to deal with medical issues reflected through images of human body, organs and cells. It is necessary to preserve the fused image in order to keep the relevant information of input images. It is also necessary to keep the fusion process away from introducing any artifacts or inconsistencies. More over image fusion techniques must provide a good quality and must enhance the applications of recent data. This paper elucidates the survey of recent literatures, which dealt medical images like magnetic resonance imaging (MRI), Computed Tomography (CT), Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) of brain. This paper reviews some of the recent medical image fusion algorithm such as Non Sampled Contourlet transform, Directive Contrast, Daubechies complex wavelet transform, Shift-invariant Shearlet transform etc. The merits and demerits of the various image fusion algorithm which developed by the authors is described in the paper. The survey emerges out the optimum fusion algorithm.

The assist device for blind people is much needed in recent days. The gadgets in recent trends are digitized that the blind people are not capable of handling digitized applications hence in our project we design text to voice converter, that converts the eBooks, audiobooks to voice format. In this project the audiobook eBooks are fed into SD card reader after that the sd card reader is interfaced and the Arduino UNO converts the text file to Audio output. The audio books can be heard in headphone\speaker using Arduino UNO. This project is low cost it will be more useful for blind people. Secure voting must be necessary to avoid the fake voting. The problem of fake voting can be solved by using Face detection and Finger vein based Electronics Voting Machine (EVM) system. In electronic voting system the details of the voters are stored; the voting date is recorded and processed digitally. Most of the existing Electronic voting machines has been developed using Radio Frequency ID. In developing countries RFID for each person is not possible due to high cost efficiency. Image processing based EVM also introduced, but it not provides accurate results for the twin persons. The EVM with finger print also not providing the accurate results. So the modified EVM with face and finger vein was introduced to obtain the satisfied result. The Raspberry Pi plays major roll in this project. It is act as a on board CPU work on the operating system called rasbian OS. The necessary hardwires like, camera, finger vein scanner, EVM are connected with Rasperry Pi. The datas of all the voters along with the images of the face and the finger vein are already stored in the system. The camera capture the picture of the person then compare with the stored data and find whether the person is authorized person or not. Once the person is authorized then the next section scan the finger and compare with the data and inform to the system that whether known or unknown. If both face and finger vein are recognized then the voter can register their vote. The fake voting can be completely avoid using this voting method.