Zainul Abdin Jaffery

Segmentation and Characterization of Brain Tumor from MR Images

The objective of this paper is to present a method to characterize a brain tumor. The authors developed a tumor characterization technique using Marker Controlled Watershed Segmentation method and region property functions using image processing toolbox. The parameters extracted are area, major and minor axis length, eccentricity, orientation, equivdiameter, solidity and perimeter. This method is quite versatile, fast and simple to use. This can be applied to all type of 2D MR Images representing all tumors irrespective of their location in human body and their size. The proposed technique has been simulated on Matlab and results are compared with experimental data obtained from diagnostic centre

Architecture of Noninvasive Real Time Visual Monitoring System for Dial Type Measuring Instrument

Noninvasive real time visual monitoring systems are more demanding in the field of automation because of their high reliability, robustness, fast execution time, portability, and flexibility. In this paper, a novel architecture of detection algorithm has been developed to identify the geometrical and statistical features of position of the pointers image from the captured image of indicating type meters in real time. In our view, a real time visual monitoring system has the following stages: 1) image acquisition; 2) image pre-processing; 3) segmentation; 4) feature extraction; 5) feature matching; and 6) display of result into graphical user interface window along with controlling decision. The geometrical, statistical, and wavelet-based image features were used to recognize the indicated value using feature matching algorithm. Also, the system controller compares the recognized value with the set value of parameters and if, it is found beyond the specified limit, it generates various alarms and controlling or tripping signals for the final control elements.

Techno-economic feasibility of HVDS concept for distribution feeder power loss minimisation

This paper presents a method to reduce the technical power loss in distribution systems. The high voltage distribution system is proposed to minimize the technical distribution losses. The analysis is done using CYMDIST. The developed methodology is carried on a Lalpura distribution feeder from the Palwal division (Haryana). The feeder is feeding to 89 Distribution transformers with 200 amperes peak load and having the length of about 76 km. The analysis reveals that converting the existing LVDS system for the agricultural load to HVDS system, there is net reduction in technical losses in the distribution system which in turn raises the efficiency of the system. Also it shows the economic viability of the proposed technique.

Real Time Visual Inspection System(RTVIS) for calibration of mechanical gauges

Real Time Visual Inspection System becoming a reliable system for quality analysis and control in various process and manufacturing industries. The important task of RTVIS in measuring instrument manufacturing industry is to prevent the inclusion of incorrect parts and to maintain quality standard. The RTVIS itself capable to handle the factors caused by positional, rotational alignment and illumination changes. In this paper we have used RGB images of dial type fuel gauges having a pointer which indicates fuel level. This image is cropped and then converted into grey scale image and binary image, displaying only black pointer by selecting proper threshold value. After interpretation and processing, the RTVIS visualizes the gauge parameters and shows the results with its artificial intelligence about the quality and correctness of the gauge under test.

Solar energy harvesting wireless sensor network nodes: A survey

Solar energy harvesting that provides an alternative power source for an energy-constrained wireless sensor network (WSN) node is completely a new idea. Several developed countries like Finland, Mexico, China, and the USA are making research efforts to provide design solutions for challenges in renewable energy harvesting applications. The small size solar panels suitably connected to low-power energy harvester circuits and rechargeable batteries provide a loom to make the WSN nodes completely self-powered with an infinite network lifetime. Recent advancements in renewable energy harvesting technologies have led the researchers and companies to design and innovate novel energy harvesting circuits for traditional battery powered WSNs, such as Texas Instruments Ultra Low Energy Harvester and Power Management IC bq25505 [see https://store.ti.com/BQ25505 for Texas Instruments (TI) Ultra Low Power Boost Charger IC bq25505 with Battery Management and Autonomous Power Multiplexor for Primary Battery in Energy Harvester Applications datasheets (2015).]. In modern days, the increasing demand of smart autonomous sensor nodes in the Internet of Things applications (like temperature monitoring of an industrial plant over the internet, smart home automation, and smart cities) requires a detailed literature survey of state of the art in solar energy harvesting WSN (SEH-WSN) for researchers and design engineers. Therefore, we present an in-depth literature review of Solar cell efficiency, DC-DC power converters, Maximum Power Point Tracking algorithms, solar energy prediction algorithms, microcontrollers, energy storage (battery/supercapacitor), and various design costs for SEH-WSNs. As per our knowledge, this is the first comprehensive literature survey of SEH-WSNs.

Maximally Stable Extremal Region Marking-Based Railway Track Surface Defect Sensing

Railway track monitoring is a challenging task to avoid railway accidents due to track failures. There are lot many issues involved in the railway accidents but the major involvement is the use of defective railway tracks. The aim of this paper is to present a novel visual inspection technique for detection, marking, and visualization of defected portion in railway tracks. In this paper, maximally stable extremal region technique is used to identify and visualize the geometrical features of the defected regions on the rail head surface in railway track images. Here, three classes of surface defects have been taken. The results are very promising and comprise all the aspects.

Advances of Broadband Power Line Communication and its application

Broadband Power Line Communication (BPLC) technology, offers a convenient, efficient and reliable medium for high frequency-data transfer for broadband access, by creating networks within existing infrastructure. As the powerline network is very noisy, complex and varying from place to place, it is very difficult to model the channel. For creating a new efficient power line communication model of the channel, it is necessary to know the characteristic, topology of the low voltage powerline. A review analysis has been given on advances, issues and applications of broadband power line communication in various fields. With this paper, we also offer a low voltage power line channel transfer function with small sets of parameters, by means of a simulation tool in the bandwidth 1-30 MHz The observations presented in the paper are important and useful for an efficient channel design of a BPLC system.

A Vision-Based System for Traffic Light Detection

Traffic detection and interpretation of its correct state is one of the most important information for developing an autonomous vehicle navigation system. Traffic light detection helps the autonomous vehicle to navigate safely in outdoor environment. In this paper, a vision-based algorithm is developed for traffic light detection and recognition. A monocular camera is used for capturing the surrounding outdoor environment. Intensity features are extracted from the templates of the traffic light and, the detection system is trained with these features. Similar features are searched in a predefine region of interest in the acquired image. Highly match candidates are considered as suitable traffic light candidate. The proposed algorithm is implemented in Labview NI-VISION system. Labview acquires data very effectively and effectively performs real-time processing. Using NI-VISION platform based system can go from design to test with minimum system changes. Adaptation of changing requirement is easy and less time consuming for Labview-based system. The algorithm is tested on different light condition images to check the reliability of system. Results show that developed algorithm is highly effective in real-time application for autonomous vehicle.

An Approach to Color Image Coding Based on Adaptive Multilevel Block Truncation Coding

Block Truncation Coding (BTC) has been considered as a prime choice in many instances because it is the simplest to implement and is quite satisfactory from the viewpoint of the resulting fidelity and compression ratio. To effectively compute multidimensional color data, an efficient expression of color data is necessary, therefore this paper presents a novel BTC algorithm called Adaptive Multilevel Block Truncation Coding (AMBTC) to achieve the optimal coding performance by adaptively choosing two-level or four-level BTC according to the edge property of the coding block. The AMBTC uses an adaptive selector level based on the sum of absolute difference (SAD) to get optimal coding performance. In order to reduce the bit rate, we utilize luminance bitmap that represents the three color bitmaps. This method improves the two-level and four-level BTC used in AMBTC. The simulation result is compared with existing conventional BTC and it is found that the proposed BTC outperforms in PSNR and compression ratio and achieves better image quality of reconstructed images.

Classifiers for the Detection of Skin Cancer

Diagnosis of skin cancer at an early stage is made possible with the highly advanced medical technology. Researchers are proficient in diagnosing skin cancer which involves the basic preprocessing but problem is faced during selection of a classifier to give best diagnose. This paper will illuminate these classifiers that can be used to detect skin cancer accompanied with their pros and cons. Also, it will throw light on future perspective of various approaches.