ANN-based Innovative Segmentation Method for Handwritten text in Assamese

Artificial Neural Network (ANN) s has widely been used for recognition of optically scanned character, which partially emulates human thinking in the domain of the Artificial Intelligence. But prior to recognition, it is necessary to segment the character from the text to sentences, words etc. Segmentation of words into individual letters has been one of the major problems in handwriting recognition. Despite several successful works all over the work, development of such tools in specific languages is still an ongoing process especially in the Indian context. This work explores the application of ANN as an aid to segmentation of handwritten characters in Assamese- an important language in the North Eastern part of India. The work explores the performance difference obtained in applying an ANN-based dynamic segmentation algorithm compared to projection- based static segmentation. The algorithm involves, first training of an ANN with individual handwritten characters recorded from different individuals. Handwritten sentences are separated out from text using a static segmentation method. From the segmented line, individual characters are separated out by first over segmenting the entire line. Each of the segments thus obtained, next, is fed to the trained ANN. The point of segmentation at which the ANN recognizes a segment or a combination of several segments to be similar to a handwritten character, a segmentation boundary for the character is assumed to exist and segmentation performed. The segmented character is next compared to the best available match and the segmentation boundary confirmed

A Soft Computing Framework for Brain Tumor Detection through MRI Images

Brain Tumor is one of the deadly diseases that has taken the lives of many people. A tumor can be benign or malignant. Benign tumors are curable if detected at the early stage. In today’s modern era of medical technology, MRI (Magnetic Resonance Imaging) has proved to be an efficient method of detecting the presence of brain tumor in the patient. Proper detection of brain tumor is necessary for further treatment of the patient which is possible through accurate segmentation of the brain. Brain segmentation plays a vital role in brain tumor detection. Over the years many researchers have proposed different methods for brain tumor detection but use of soft computing tool is much more preferred as far as human error is concerned. Here, a method of classification of images with and without tumor is dictated using Artificial Neural Network (ANN). The ANN has been configured to detect the presence of tumor by using various parameters of Gray-Level Co-occurrence Matrix (GLCM).Keywords:Brain tumor, MRI, pre-processing, soft computing, neural networ

Facial expression based emotion detection-A Review

Emotion detection is the task of recognizing a person’s emotion state. Understanding facial expression accurately is one of the challenging task for interpersonal relationship. Automatic emotion detection using facial expressions recognition is now a main area of interest within various fields such as computer vision, medicine and psychology. Various feature extraction techniques have been developed for recognition of expression from static images as well as real time videos. Artificial Neural Network (ANN) based detection for emotion like anger, confusion, happy, sad, annoyed, stressed etc. is now a days, gathering more popularity among the researchers as it provides better results. Human emotion can be detected image through digital processing. Few work done on emotion detection, those are published recently reviewed are summarizes here briefly.Keywords—Emotion, interpersonal, facial expression, ANN, Recognition, extraction, digital processin

A study on different linear and non-linear filtering techniques of speech and speech recognition

In any signal noise is an undesired quantity, however most of thetime every signal get mixed with noise at different levels of theirprocessing and application, due to which the information containedby the signal gets distorted and makes the whole signal redundant.A speech signal is very prominent with acoustical noises like bubblenoise, car noise, street noise etc. So for removing the noises researchershave developed various techniques which are called filtering. Basicallyall the filtering techniques are not suitable for every application,hence based on the type of application some techniques are betterthan the others. Broadly, the filtering techniques can be classifiedinto two categories i.e. linear filtering and non-linear filtering.In this paper a study is presented on some of the filtering techniqueswhich are based on linear and nonlinear approaches. These techniquesincludes different adaptive filtering based on algorithm like LMS,NLMS and RLS etc., Kalman filter, ARMA and NARMA time series applicationfor filtering, neural networks combine with fuzzy i.e. ANFIS. Thispaper also includes the application of various features i.e. MFCC,LPC, PLP and gamma for filtering and recognition

A review of Terahertz technology and Metamaterial based electromagnetic absorber at Terahertz band

 Terahertz (THz) technology, a new step towards the wireless communication is a recent topic of research. THz radiation has unique properties which make it better than microwaves, infrared, X-rays, etc. These radiations have wide applications in various fields like imaging, spectroscopy, security, biomedicine, sub-millimeter astronomy, in communication, etc. THz radiation sources and detectors play a vital role in the THz communication system.  The sources and detectors for THz radiation are still in a developing stage. As in naturally occurring materials, there is lack of good terahertz characteristic, so researchers are moving towards artificial one, i.e., the metamaterial based design. Metamaterial based design of generation and detection of THz radiation is the recent demands in the field of THz communication. Hence, we are focussing on the metamaterial based terahertz transmitter and receiver. So in this paper, a brief study of the THz technology based on metamaterial has been carried out and presented here

Automatic RADAR Target Recognition System at THz Frequency Band. A Review

The development of technology for communication in the THz frequency band has seen rapid progress recently. Due to the wider bandwidth a THz frequency RADAR provides the possibility of higher precision imaging compared to conventional RADARs. A high resolution RADAR operating at THz frequency can be used for automatically detecting and segmenting concealed objects. Recent advancements in THz circuit integration have opened up a wide range of possibilities for on chip applications, like of security and surveillance. The development of various sources and detectors for generation and detection of THz frequency has been driven by other techniques such as spectroscopy, imaging and impulse ranging. One of the central vision of this type of security system aims at ambient intelligence: the computation and communication carried out intelligently. The need for higher mobility with limited size and power consumption has led to development of nanotechnology based THz generators. In addition to this some of the soft computing tools are used for detection of radar target automatically based on some algorithms named as ANN, RNN, Neuro-Fuzzy and Genetic algorithms. This review article includes UWB radar for THz signal, its characteristics and application, Nanotechnology for THz generation and issues related to ATR

Low Resource FPGA Based Time-to-Digital Converter

For the precise measurement of the time difference between the arrival of different signals coming from the different channels, the time-to-digital converter (TDC) implemented in Field Programmable Gate Array (FPGA) is a very useful device. The TDC implemented so far are  basically tapped delay lines which provides a resolution of about 10 ps however such high resolution is necessary for some specific applications. So a low resource TDC implemented in FPGA is preferred which helps to measure the time difference between the signals.Keywords: analog-to-digital converter (ADC), resolution, DPLL, clock generation, jitte

Counter-Based and MUX-Based Design of DPLL, a Comparative Study

The design of modern day communication system emphasizes on transmission and proper reception of data at minimum possible error rates and also at the same time on maintenance of high degrees of precision. But there are additional factors that add to it such as the operating speeds of the communication device developed should be compatible with the other sub-systems of the setup. Also, the design complexity of the device and the cost of design should be minimum. So, based on the various factors as mentioned above, a situation arises where a number of designs can be put forward for the same device having their sets of merits and demerits. As such, an analysis of these different designs is essential to derive an optimal solution which is the main objective of this work. Considering the various constraints at hand, we would like to put forward a comparative study between two different designs of the communication receiver device DPLL, namely the counter based DPLL and Multiplexer based DPLL design which brings to light the merits of one design over the other in terms of key parameters such asspeed, design, complexity, hardware requirement etc.Keywords: Multiplexer, oscillator, detector, phase, recover

HOME AUTOMATION SYSTEM.

Home automation system is becoming popular day by day all-over the world. Starting from simple home to large industrial setup everywhere Home Automation is used in a large number. With the advancement of technologies home automation system are gradually advancing more and more, making the life of every individual smoother and easier with minimizing the work load. Home automation refers to the automatic and electronic control of household appliances, features and activities which is initially developed with the aim to provide supporting system for the elderly and disabled, especially those who live alone but now a days it also fulfil the requirement of a large number of population seeking luxury and sophisticated home automation platform. The main objective of the project is to provide the necessary freedom of controlling devices in home or industry like tube light, electrical bulbs, electrical fan, AC etc. automatically using different sensors like PIR, DHT 11, wit the Arduino UNO platform by sensing the presence of individual. The device is made smart enough to detect human presence using PIR sensor and measuring different other parameters like daylight, temperature etc to control Electrical bulbs and the speed of fan. The proposed prototype also come with a LCD display to make the user to see the different values of measured parameters like temperature etc. The device also enables the user to manually control different activities like ON/OFF lights and speed of fan. The device is also a cost effective model to make it possible to implement by everyone according to there requirements