Anil Bavaskar

Emergencyalertsystem Wearabledeviceforwomen Safety

Design Engineering, Jul 7, 2021

FPGA Implementation of high performance entropy encoder for H.264 Video CODEC

In information theory an entropy encoding is a lossless data compression scheme that is independe... more In information theory an entropy encoding is a lossless data compression scheme that is independent of the specific characteristics of the medium. One of the main types of entropy coding creates and assigns a unique prefix-free code to each unique symbol that occurs in the input. These entropy encoders then compress data by replacing each fixedlength input symbol with the corresponding variable-length prefix-free output codeword. The length of each codeword is approximately proportional to the negative logarithm of the probability. Therefore, the most common symbols use the shortest codes. Context-based adaptive variable-length coding (CAVLC) is an important feature of the latest video coding standard H.264/AVC. Context-adaptive variable-length coding (CAVLC) is a form of entropy coding used in H.264/MPEG-4 AVC video encoding. It is an inherently lossless compression technique, like almost all entropy-coders. In H.264/MPEG-4 AVC, it is used to encode residual, zigzag order, blocks of transform coefficients. It is an alternative to context-based adaptive binary arithmetic coding (CABAC). CAVLC requires considerably less processing to decode than CABAC, although it does not compress the data quite as effectively. CAVLC is supported in all H.264 profiles, unlike CABAC which is not supported in Baseline and Extended profiles. The coding technique using conventional CAVLC based on area efficient design, the second is on low power design architecture will lead to low throughput. In this project, an efficient CAVLC design is proposed. The main concept is the FPGA based pipelining scheme for parallel processing of two 4x4 blocks. When one block is processed by the scanning engine to collect the required symbols, its previous block is handled by the coding engine to translate symbols into bit stream. Our block based pipelined architecture doubles the throughput of CAVLC at high bit rates.

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Automatic Classification of Brown Spot and Blast Diseases of Rice Using Vegetation Indices Based Segmentation

Rice is widely cultivated economical crop in the world. India is an agricultural country and plan... more Rice is widely cultivated economical crop in the world. India is an agricultural country and plant disease plays key role in the production of agricultural product. Earlier detection will help to improve the quality and quantity of the product.The proposed system is an identification of brown spot and blast disease of rice.Plant disease detection is emerging field in India as agriculture is important sector in economy and social life.Earlier unscientific method were in existence. Automatic identification of plant diseases is the new challenging area for the researchers. One of the most important steps in automatic identification of plant diseases is to extract the infected region from the normal portion of the plant. Studding the infected leaves it has been observed that the greenness of the infected portion of the leaves changes significantly with respect to the normal leaves. Vegetation indices (VI) are some metric used for the remote sensing images to measure the greenness. Thus VIs are computed from the acquired images of the infected plant. These VI are then used to extract the infected portion from the acquired visual images.

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Denoising of Images using wavelet Bayesian Network

This paper presents a ne w wavelet-based image denoising method which is "Bayesian Network" are p... more This paper presents a ne w wavelet-based image denoising method which is "Bayesian Network" are probably the most popular type of graphical model.In this paper our objective is to construct a Bayesian Network from a single image for denoising purpose.The construction of a Bayesian Network involves prior knowledge of the probability relationships between the variables of interest.Learning approaches are widely used to construct Bayesian Network that best represent the joint probabilities of training data. In this method the data is represented in wavelet domain and restriciting the space of possible networks by using certain techniques.The proposed approach exploits a hidden Bayesian network constructed from wavelet coefficient to model the prior probability of the original image.Then use the belief propagation (BP) algorithm which estimates a coefficient of an image as the maximum-a-posterior (MAP) estimator to derive the denoised wavelet coefficient. We show that if the network is a spanning tree,the standard BP algorithm can perform MAP estimation efficiently.Our experiment results demonstrate that in terms of the peak-signal-to-noise ratio and perceptual quality the reconstructed image has been improved.The planned approach out performs state-of-the-art algorithms on several images mostly in the textured regions, with various amounts of white Gaussian noise.

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Fruit Detection Using Morphological Image Processing Technique

Agriculture is mother of all culture, due to the increase demand in agriculture industries the ne... more Agriculture is mother of all culture, due to the increase demand in agriculture industries the need to effectively grow a plant an increase its yield is very important. In this study, a method is proposed to detect fruits on tree using image processing technique. For counting the fruits, the main problem is variable lighting conditions for the environment in outdoor. The additional problem is the occlusion of fruits by Leaves, branches, and the other fruits. In the proposed method these problems are also examined. External appearance is one of the most significant attributes for fruits when consumers decide to choose or reject them, thus packinghouses need to adopt appropriate systems that are capable of detecting the skin defects for fruits before packing them into batches and reaching the end consumers. In this paper we also differentiate the healthy fruits and fruits which are infected by diseases.

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Fusion Based Edge Detection and Segmentation of Color Spaces

Image Fusion is a process of combining the relevant information from a set of images into a singl... more Image Fusion is a process of combining the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Also the choice of a color space is of great importance form any computer vision algorithms (e.g. edge detection and object recognition).This paper presents efficient segmentation, edge detection approach, based on a fusion procedure which aims at combining several segmentation images associated to simpler partition models in order to finally get a more reliable and accurate segmentation. Image fusion techniques can improve the quality and increase the application of these data. The objective of Image fusion is to combine the information of the number of images of the same scene from different sensors or the images with focus on different objects. In this paper an introductory approach to some of the image fusion methods has been taken. End edge detection is one of the most commonly used operations in image analysis. In this paper, we present methods for edge segmentation of natural images; we used several techniques for this category;

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Emergencyalertsystem Wearabledeviceforwomen Safety

Design Engineering, Jul 7, 2021

A Review on Emergency Alert System Wearable Device for Women Safety

This review paper explaining technological solutions for women safety considering state of the ar... more This review paper explaining technological solutions for women safety considering state of the art in various categories of the domain. The categories for which the systems are explored are sessile systems, mobile systems, intelligent systems and other systems. After the detailed study of the existing work done in the area, desirable characteristics of a system for safety of women are identified and tabularized. Moreover, we have also identified responses of women under various categories based on identified characteristic which is illustrated graphically at the end of paper. This paper contributes three things, state of the art in various categories, ideal characteristics of system for women safety, and survey of women’s feedback for future development of women’s safety system.

FPGA Implementation of high performance entropy encoder for H.264 Video CODEC

ICSESD-2017

In information theory an entropy encoding is a lossless data compression scheme that is independe... more In information theory an entropy encoding is a lossless data compression scheme that is independent of the specific characteristics of the medium. One of the main types of entropy coding creates and assigns a unique prefix-free code to each unique symbol that occurs in the input. These entropy encoders then compress data by replacing each fixedlength input symbol with the corresponding variable-length prefix-free output codeword. The length of each codeword is approximately proportional to the negative logarithm of the probability. Therefore, the most common symbols use the shortest codes. Context-based adaptive variable-length coding (CAVLC) is an important feature of the latest video coding standard H.264/AVC. Context-adaptive variable-length coding (CAVLC) is a form of entropy coding used in H.264/MPEG-4 AVC video encoding. It is an inherently lossless compression technique, like almost all entropy-coders. In H.264/MPEG-4 AVC, it is used to encode residual, zigzag order, blocks of transform coefficients. It is an alternative to context-based adaptive binary arithmetic coding (CABAC). CAVLC requires considerably less processing to decode than CABAC, although it does not compress the data quite as effectively. CAVLC is supported in all H.264 profiles, unlike CABAC which is not supported in Baseline and Extended profiles. The coding technique using conventional CAVLC based on area efficient design, the second is on low power design architecture will lead to low throughput. In this project, an efficient CAVLC design is proposed. The main concept is the FPGA based pipelining scheme for parallel processing of two 4x4 blocks. When one block is processed by the scanning engine to collect the required symbols, its previous block is handled by the coding engine to translate symbols into bit stream. Our block based pipelined architecture doubles the throughput of CAVLC at high bit rates.

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Research Article on Image Denoising

International Journal of Scientific Research in Science and Technology, 2017

Implementation of FPGA-Based General Purpose Artificial Neural Network

The usage of the FPGA (Field Programmable Gate Array) for neural network implementation provides ... more The usage of the FPGA (Field Programmable Gate Array) for neural network implementation provides flexibility in programmable systems. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI design. In addition, artificial neural network based on FPGAs has fairly achieved with classification application. The programmability of reconfigurable FPGAs yields the availability of fast special purpose hardware for wide applications. Its programmability could set the conditions to explore new neural network algorithms and problems of a scale that would not be feasible with conventional processor. The goal of this work is to realize the hardware implementation of neural network using FPGAs. Digital system architecture is presented using Very High Speed Int...

Fruit Detection Using Image Processing Technique

International Journal of Scientific Research in Science and Technology, 2017

Denoising of Images using wavelet Bayesian Network

This paper presents a ne w wavelet –based image denoising method which is “Bayesian Network” are ... more This paper presents a ne w wavelet –based image denoising method which is “Bayesian Network” are probably the most popular type of graphical model.In this paper our objective is to construct a Bayesian Network from a single image for denoising purpose.The construction of a Bayesian Network involves prior knowledge of the probability relationships between the variables of interest.Learning approaches are widely used to construct Bayesian Network that best represent the joint probabilities of training data. In this method the data is represented in wavelet domain and restriciting the space of possible networks by using certain techniques.The proposed approach exploits a hidden Bayesian network constructed from wavelet coefficient to model the prior probability of the original image.Then use the belief propagation (BP) algorithm which estimates a coefficient of an image as the maximum-a-posterior (MAP) estimator to derive the denoised wavelet coefficient. We show that if the network is...

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Iot Based Renewable Solar Monitoring System

Presently a day’s sustainable power source frameworks are winding up most ideal approach to creat... more Presently a day’s sustainable power source frameworks are winding up most ideal approach to create power. With headway of advancements the expense of sustainable power source types of gear is going down all inclusive empowering extensive scale sun oriented photovoltaic establishments. Significant piece of sustainable power source is sun oriented vitality. Because of its decentralized nature it is exceptionally hard to screen sun oriented power plants with existing unified SCADA(Supervisory Control And Data Acquisition) frameworks. We built up a model for usage of new practical strategy dependent on IoT to screen a sun oriented photovoltaic plant for execution assessment utilizing open source devices and assets like Arduino and Ubidots. Ubidots is a SaaS (Software as a Service) stage which gives space on Web to screen our parameters. Ubidots gives all administrations to free of expense which spares parcel of speculation on Website planning and support. We focused on minimal effort fr...

Real-Time IoT-Based Health Care Monitoring for Prediction and Analysis

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Automatic Classification of Brown Spot and Blast Diseases of Rice Using Vegetation Indices Based Segmentation

Rice is widely cultivated economical crop in the world. India is an agricultural country and plan... more Rice is widely cultivated economical crop in the world. India is an agricultural country and plant disease plays key role in the production of agricultural product. Earlier detection will help to improve the quality and quantity of the product.The proposed system is an identification of brown spot and blast disease of rice.Plant disease detection is emerging field in India as agriculture is important sector in economy and social life.Earlier unscientific method were in existence. Automatic identification of plant diseases is the new challenging area for the researchers. One of the most important steps in automatic identification of plant diseases is to extract the infected region from the normal portion of the plant. Studding the infected leaves it has been observed that the greenness of the infected portion of the leaves changes significantly with respect to the normal leaves. Vegetation indices (VI) are some metric used for the remote sensing images to measure the greenness. Thus ...

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On IOT Architecture For Vehicle Tracking System

The primary objective of this work is to review the vehicle tracking system, discuss the challeng... more The primary objective of this work is to review the vehicle tracking system, discuss the challenges in Internet of Things (IoT) based vehicle tracking system. IoT is used to get intellectual connecting the objects with each other via information sensing in the physical world and broadcasting devices linked with the internet.This paper provides a comprehensive investigation on vehicle tracking system in association with the IoT and Big Data Analytics. This paper analyze the challenges pertaining to the IoT based Vehicle tracking system.This paper provides the novel methodology for assessing the quality of vehicle tracking system and identifies opportunity for future research in this area. Applications: The importance of QoE can be realized in vehicle tracking system for the improving the performance of the surveillance system.

Fruit Detection Using Morphological Image Processing Technique

ICSESD-2017, 2017

Agriculture is mother of all culture, due to the increase demand in agriculture industries the ne... more Agriculture is mother of all culture, due to the increase demand in agriculture industries the need to effectively grow a plant an increase its yield is very important. In this study, a method is proposed to detect fruits on tree using image processing technique. For counting the fruits, the main problem is variable lighting conditions for the environment in outdoor. The additional problem is the occlusion of fruits by Leaves, branches, and the other fruits. In the proposed method these problems are also examined. External appearance is one of the most significant attributes for fruits when consumers decide to choose or reject them, thus packinghouses need to adopt appropriate systems that are capable of detecting the skin defects for fruits before packing them into batches and reaching the end consumers. In this paper we also differentiate the healthy fruits and fruits which are infected by diseases.

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Solitary pulmonary nodule detection in lung image using image processing

International Journal of Advance Research, Ideas and Innovations in Technology, 2018

Cancer is a group of diseases begins in cells that are the basic building blocks of a body. There... more Cancer is a group of diseases begins in cells that are the basic building blocks of a body. There are different types of cancers but all starts with the cells growing out of control. The type and stage of cancer can be determined by determining where the abnormal growth occurs in the body and the type of cells that start to grow abnormally. The type of cancers often found in adults is endometrial cancer, skin cancer, lung cancer, ovarian cancer and breast cancer. Of these cancers, the most common type of cancer is the Lung cancer. This type of cancer is common due to smoking. The earlier it is detected; the better is the chance of curing. This review examines and summarizes various techniques and algorithms used for lung cancer detection.

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