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S. Muruganand

Bio: S. Muruganand is an academic researcher from Bharathiar University. The author has contributed to research in topics: Median filter & GSM. The author has an hindex of 6, co-authored 9 publications receiving 67 citations.

Papers
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Journal Article
TL;DR: The recognition approach identifies the shape and texture features of the medicinal leaves using MATLAB, and extracts certain features from the inputted leaf images later using different methods like thresholding, segmentation.
Abstract: Medicinal leaves have been widely used in medicine, Pharamastic and Cosmetic industry. Knowing of the medicinal leaves are very critical in the futures. Nevertheless, the current way of identification and determination of the type of medicinal leaves is still being done manually and prone to human error. Leaves species is essential since this will improve medicinal species classification efficiency. In this paper the recognition approach identifies the shape and texture features of the medicinal leaves. In this paper MATLAB is used. First, we extract certain features from the inputted leaf images, later using different methods like thresholding, segmentation. After preprocessing the image data are applied to Neural Network. And compared with several trained databases. Thus this paper analysis the medicinal leaves with a successfully using image processing.

18 citations

Journal ArticleDOI
TL;DR: The design of a simple low cost microcontroller based temperature monitoring system using GSM technique and ADC is used because microcontroller works with digital inputs.
Abstract: paper describes the design of a simple low cost microcontroller based temperature monitoring system using GSM technique. The temperature monitoring system using GSM undergoes three stages signal conditioning circuit, analog to digital converter and with GSM Modem the message is send to mobile.ADC is used because microcontroller works with digital inputs. GSM modem can be used to send and receive SMS through AT commands. At the transmitter side, the user sends an SMS to the GSM modem using AT commands. The LM35 is an integrated circuit sensor that can be used to measure temperature with electrical output proportional to the temperature. The LM35 sensor is connected to PIC microcontroller and varying temperature is sent to GSM modem, which is simultaneously displayed in LCD. The GSM modem performs the operation of sending message to a particular SIM number .GSM technology provides users with high quality signal and speech channels, giving them access to high quality digital communication at very affordable rates. GSM network operators can provide their customers with cheaper calling and text messing options.

12 citations

Journal ArticleDOI
TL;DR: The aim of the paper is to find the number and English alphabets in the symbol of times new roman, arial, arian block size of 72, 48.
Abstract: Optical character recognition is getting more and more useful in daily life for various purposes. The aim of the paper is to find the number and English alphabets in the symbol of times new roman, arial, arial block size of 72, 48.Many researches have been done on many types of characters by using different approaches. In this recognition system was implemented by using of principal component analysis (PCA) algorithm. This algorithm is based on an Eigen value and Euclidean distance. PCA is practical and standard statistical tool in modern data analysis that has found application in different areas such as face recognition, image compression, and neuroscience.

12 citations

01 Jan 2013
TL;DR: This work presents a hierarchical grading method applied to the tomatoes that can identify the good and bad tomatoes with a very high accuracy successfully using image processing.
Abstract: The ability to identify the tomatoes based on quality in the food industry which is the most important technology in the realization of automatic tomato sorting machine in order to reduce the work of human and also time consuming. This work presents a hierarchical grading method applied to the tomatoes. In this work the identification of good and bad tomatoes is focused on the methods using MATLAB. First we extract certain features from the input tomato image, later using different method like thresholding, segmentation, k-means clustering and thus we get related databases. Comparing several trained databases, we get a specific range for the good and bad tomatoes. From the proposed range we can identify the good and bad tomatoes. Thus this paper analysis the good and bad tomatoes with a very high accuracy successfully using image processing.

8 citations

Journal Article
TL;DR: A filtering technique to efficiently suppress the noise in the human dental Digital X-ray images of real database from hospitals to diagnosis the dental disorder accurately by improving the quality of the image is presented.
Abstract: This paper work based on Quality improvement analysis of digital dental X-ray image. If it is one of the active research areas in Digital Image Processing (DIP), it is removal of noise from images. Taking this into consideration this paper presents a filtering technique to efficiently suppress the noise in the human dental Digital X-ray images of real database from hospitals. During the removal of noise in an image here using various filters in image processing techniques: The image is affected by several noisy pixels with (1) Impulse noise, (2) Speckle noise and (3) Poisson noise . Many different filtering techniques have been proposed for the removal of such noises from digital images. The proposed project is to reduce noise in digital dental digital X-ray image to diagnosis the dental disorder accurately by improving the quality of the image. The obtained image can be processed by using MATLAB. The result shows the proposed method proves better than the existing method by using PSNR.

8 citations


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Journal ArticleDOI
TL;DR: A novel plant species classifier based on the extraction of morphological features using a Multilayer Perceptron with Adaboosting is introduced, which outperformed the state-of-the-art algorithms.
Abstract: Plant species detection aims at the automatic identification of plants. Although a lot of aspects like leaf, flowers, fruits, seeds could contribute to the decision, but leaf features are the most significant. As a plant leaf is always more accessible as compared to other parts of the plants, it is obvious to study it for plant identification. The present paper introduced a novel plant species classifier based on the extraction of morphological features using a Multilayer Perceptron with Adaboosting. The proposed framework comprises pre-processing, feature extraction, feature selection, and classification. Initially, some pre-processing techniques are used to set up a leaf image for the feature extraction process. Various morphological features, i.e., centroid, major axis length, minor axis length, solidity, perimeter, and orientation are extracted from the digital images of various categories of leaves. Different classifiers, i.e., k-NN, Decision Tree and Multilayer perceptron are employed to test the accuracy of the algorithm. AdaBoost methodology is explored for improving the precision rate of the proposed system. Experimental results are obtained on a public dataset (FLAVIA) downloaded from http://flavia.sourceforge.net/. A precision rate of 95.42% has been achieved using the proposed machine learning classifier, which outperformed the state-of-the-art algorithms.

59 citations

01 Jan 2013
TL;DR: The aim of this paper is to present a design that can automatically detect and stop gas leakage in vulnerable premises and provide the design approach on both software and hardware.
Abstract: Gas leakage is a major problem with industrial sector, residential premises and gas powered vehicles like CNG (compressed natural gas) buses, cars. One of the preventive methods to stop accident associated with the gas leakage is to install gas leakage detection kit at vulnerable places. The aim of this paper is to present such a design that can automatically detect and stop gas leakage in vulnerable premises. In particular gas sensor has been used which has high sensitivity for propane (C3H8) and butane (C4H10). Gas leakage system consists of GSM (Global System for mobile communications) module, which warns by sending SMS. However, the former gas leakage system cannot react in time. This paper provides the design approach on both software and hardware.

47 citations

Journal ArticleDOI
Li Chunlin1, Guo Haowei1, Bangzheng Zong1, Puming He1, Fan Fangyuan1, Gong Shuying1 
TL;DR: Principal components analysis result showed that there is potential correlation between specific spectral regions and the presence of polyphenols and alkaloids, and NIR technique is a practical method for rapid and non-destructive discrimination of special-grade flat green tea with chemical support.

46 citations

Journal ArticleDOI
TL;DR: A novel recurrent mechanism as well as a solution for filtering IN based on Lyapunov stability theory is proposed to establish an adaptive online IN filter (AOINF) and surveys are performed to evaluate the proposed method.
Abstract: In many real applications, building and updating adaptive neuro-fuzzy inference system (ANFIS) based on noisy measuring data sources need to be performed such that the filtering impulse noise (IN) from the initial datasets (IDSs) and establishing the ANFIS via the filtered IDS are carried out simultaneously. Focused on this purpose, in this paper, a novel recurrent mechanism as well as a solution for filtering IN based on Lyapunov stability theory is proposed to establish an adaptive online IN filter (AOINF). Using the AOINF, kernel fuzzy-C-means clustering method, and the least mean squares method, a cluster data space deriving from the filtered IDS is created to which the ANFIS is then formed. The recurrent mechanism executes filtering IN to build ANFIS and using the ANFIS as an updated-filter to filter IN synchronously until either the ANFIS converges to the desired accuracy or a stop condition is satisfied. Surveys, including identifying dynamic response of a magnetorheological damper via measuring datasets, are performed to evaluate the proposed method.

32 citations

Journal ArticleDOI
TL;DR: This study demonstrated that the handheld system combined with a suitable chemometric and feature information selection method could successfully be used for the rapid and efficient discrimination of CDBT rankings.
Abstract: The evaluation of Chinese dianhong black tea (CDBT) grades was an important indicator to ensure its quality. A handheld spectroscopy system combined with chemometrics was utilized to assess CDBT from eight grades. Both variables selection methods, namely genetic algorithm (GA) and successive projections algorithm (SPA), were employed to acquire the feature variables of each sample spectrum. A partial least-squares discriminant analysis (PLS-DA) and support vector machine (SVM) algorithms were applied for the establishment of the grading discrimination models based on near-infrared spectroscopy (NIRS). Comparisons of the portable and benchtop NIRS systems were implemented to obtain the optimal discriminant models. Experimental results showed that GA-SVM models by the handheld sensors yielded the best predictive performance with the correct discriminant rate (CDR) of 98.75% and 100% in the training set and prediction set, respectively. This study demonstrated that the handheld system combined with a suitable chemometric and feature information selection method could successfully be used for the rapid and efficient discrimination of CDBT rankings. It was promising to establish a specific economical portable NIRS sensor for in situ quality assurance of CDBT grades.

20 citations