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Institution

Chittagong University of Engineering & Technology

EducationChittagong, Bangladesh
About: Chittagong University of Engineering & Technology is a education organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Renewable energy & Dielectric. The organization has 1200 authors who have published 1444 publications receiving 10418 citations. The organization is also known as: Engineering College, Chittagong & Bangladesh Institute of Technology, Chittagong.


Papers
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Proceedings ArticleDOI
01 Dec 2017
TL;DR: The experimental result reveals that the proposed framework for digital electric meter reading recognition is practical and effective and based on the HVB patterns the digital meter reading sequence is recognized.
Abstract: Digital meter reading recognition from a digital electric meter image is the key step in the field of digital image processing to evaluate the meter readings from different environmental conditions automatically This work has gain important for the purpose of automatic generation of electric bill from digital electric meter image In this regard, a digital electric meter reading recognition framework is proposed in this paper For that initially, the input image is normalized and converted to YCbCr image As the digital electric meter reading region is resolute with color light, especially green, the reading region is extracted from YCbCr image based on the value of the Cb and Cr After that, Canny edge operator is employed on the extracted region to find the edge image In this edge image, the individual digit's edge gaps are filled up through the morphological operation to find individually connected digit edge image These individual digits are segmented from an edge image through the vertical projection Furthermore, the individually segmented digits are filled and thinned to detect the shapes of the digits From these segmented digit shapes the Horizontal and Vertical Binary (HVB) pattern features are extracted This is the key contribution of this paper Finally, based on the HVB patterns the digital meter reading sequence is recognized The experimental result reveals that the proposed framework is practical and effective

15 citations

Proceedings ArticleDOI
18 May 2012
TL;DR: A remote exploration and control system has been developed using web Application, web server, database, GSM network, and Android mobile phone that automatically implements command like capturing picture and upload the captured picture to the server and control electrical devices.
Abstract: A remote exploration and control system has been developed using web Application, web server, database, GSM network, and Android mobile phone. Web application is used to control remotely an Android mobile phone and electrical devices connected with the mobile phone. Firstly, command is sent from the web Application and saved in database. The Android mobile phone reads the sent command from database and performs predefined procedure to execute the command and hence, generate outcome due to execution of the command. Thus, this system can be used as an exploration and control system because remote mobile phone automatically implements command like capturing picture and upload the captured picture to the server and control electrical devices. Command is implemented to capture picture automatically of the surrounding location and upload it to server. It can also send automatically GPS location of the mobile phone to server's database. So, it can be used to detect the device's geographical location and collateral condition. Hence, it can be used in monitoring as well as in security system. Finally, command is implemented for generating DTMF tone signal on Android phone. A DTMF detection circuit, interfaced with mobile phone, can automatically detect the DTMF tone signal and generates 4 bit digital code output. This digital output code can be utilized to control any electrical device.

15 citations

Proceedings ArticleDOI
17 May 2013
TL;DR: This paper has used linear support vector machine (SVM) for classification of object and non-object data and compared performance of the proposed method with other state of the art shape feature descriptors based object recognition methods and demonstrated better performance over them.
Abstract: Object recognition in real scenes is a central problem in computer vision. In this paper we propose a new approach for shape based recognition of objects in real scenes. This approach uses moment invariants for identification of shape features. Moment Invariants are functions of central moments. They are invariant against linear transformations such as rotation, translation and scaling. Therefore, their integration provides recognition of objects in real scenes with different pose and appearances. In this way, the proposed approach does not only provide invariant object recognition, but also capable of dealing with challenges like variation in pose and appearances. We have used linear support vector machine (SVM) for classification of object and non-object data. With qualitative and quantitative experimental evaluation on standard INRIA Pedestrian dataset, we have compared performance of the proposed method with other state of the art shape feature descriptors based object recognition methods and demonstrated better performance over them.

15 citations

Journal ArticleDOI
TL;DR: In this article, the effects of using five different adhesive materials with an externally gold-screened microstructure fiber plasmonic sensor within the refractive index (RI) sensing range of 1.37-1.40.
Abstract: The adhesive layer plays a significant role in the fabrication process of plasmonic nanoantennas, micro-biosensors, nanostructures, solar cells, etc., as it delivers support to plasmonic material coating. This article discusses a study on the effects of using five different adhesive materials with an externally gold-screened microstructure fiber plasmonic sensor within the refractive index (RI) sensing range of 1.37–1.40. Numerical analyses are conducted to examine the effects of using titanium dioxide (TiO2), tantalum pentoxide (Ta2O5), indium tin oxide (ITO), zinc oxide (ZnO), and SU-8 3000 photoresist to support gold covering on the exterior portion of the fiber. The influences of each of the adhesive materials are investigated with respect to the sensor’s sensitivity for thickness variations between 5 and 20 nm. Without any adhesive layer, the proposed sensor exhibits about 1136.10 RIU−1 of amplitude interrogated sensitivity (AIS) at RI of 1.38, 14,500 nm/RIU of wavelength interrogated sensitivity (WIS), and 6.89 × 10–6 RIU of resolution at RI of 1.39. According to the analyses, it is observed that the AIS of the sensor decreases as the thickness of the adhesive layer increases. Moreover, with 5 nm of TiO2, Ta2O5, ITO, ZnO, and SU-8 3000, photoresist adhesive layers with gold, respectively, 9.29%, 7.13%, 12.38%, 5.85%, and 1.17% reductions in the AIS of the sensor have been found.

15 citations


Authors

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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20234
202240
2021243
2020241
2019228
2018119