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Author

Ramachandra A C

Bio: Ramachandra A C is an academic researcher from Alpha College of Engineering. The author has contributed to research in topics: Biometrics & Histogram equalization. The author has an hindex of 3, co-authored 6 publications receiving 30 citations.

Papers
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Journal ArticleDOI
TL;DR: The Euclidian Distance (ED) is used in matching section to compare test biometric in the database, it is observed that the values of EER and TSR are better in the case of proposed algorithm compared to individual transformation domain techniques.
Abstract: Bimodal biometric used to authenticate a person is more accurate compared to single biometric trait. In this paper we propose Feature Level Fusion based Bimodal Biometric using Transformation Domine Techniques (FLFBBT). The algorithm uses two physiological traits viz., Fingerprint and Face to identify a person. The Region of Interest (ROI) of fingerprint is obtained using preprocessing. The features of fingerprint are extracted using Dual Tree Complex Wavelet Transforms (DTCWT) by computing absolute values of high and low frequency components. The final features of fingerprint are computed by applying log on concatenated absolute value of high and low frequency components. The face image is preprocessed by cropping only face part and Discrete Wavelet Transforms (DWT) is applied. The approximation band coefficients are considered as features of face. The fingerprint and face image features are concatenated to derive final feature vector of bimodal biometric. The Euclidian Distance (ED) is used in matching section to compare test biometric in the database, it is observed that the values of EER and TSR are better in the case of proposed algorithm compared to individual transformation domain techniques.

11 citations

Proceedings ArticleDOI
01 Mar 2016
TL;DR: This paper studied various methods of Histogram Equalization, the different types are briefly explained and placed in chronological order in table.
Abstract: Image Enhancement is the process of improving the image quality for better visibility of images. The visibility and look of image will be decided by human eyes, which varies from person to person. The images resulted by quality measures made by hardware and software may not be always good and are not having natural look. Many methods are introduced to enhance images. Histogram Equalization is the method in which, the histograms of the input images are altered to obtain the enhanced images. In this paper, we studied various methods of Histogram Equalization, the different types are briefly explained and placed in chronological order in table.

11 citations

01 Jan 2009
TL;DR: Signature Verification using Graph Matching and Cross-Validation Principle (SVGMC) algorithm is proposed and better Equal Error Rate (EER) is obtained for skilled and random forgeries.
Abstract: Identification of a person depending on his physiological or behavioral characteristics is done using Biometric System. Signature verification is a commonly used biometric method and is widely used for financial transactions. In this paper, we propose Signature Verification using Graph Matching and Cross-Validation Principle (SVGMC) algorithm. Preprocessing is carried out to extract signature feature to obtain high resolution for smaller normalization box. The identical measure between two signatures in the database is determined by (i) Bipartite graph G, (ii) Complete matching in G and (iii) Minimum Euclidean distance. An optimum threshold value is determined using Cross-validation technique to select reference signatures. Pre-processing is performed on the given signature to extract test feature. Then the test feature is compared with the threshold value to verify the test signature. Better Equal Error Rate (EER) is obtained for skilled and random forgeries.

8 citations

Proceedings ArticleDOI
28 Dec 2022
TL;DR: In this article , a bottom-hat-top-hat paradigm for morphology preprocessing to deal with noise and non-uniform light is proposed, which effectively restores all important aspects in all dimensions and dimensions by breaking the images down into the Low-pass (LP) and High-Pass (HP) subbands.
Abstract: Medical image fusion (MIF), with its numerous medical uses for precisely diagnosing medical imaging, has attracted meticulous attention. The fused picture disadvantages from weak contrast, uneven lighting, the existence of noise, and incorrect fusion procedures, leading to an insufficient sparse representation of significant characteristics. Various MIF approaches have been presented to date. This study suggests a bottom-hat-top-hat paradigm for morphology preprocessing to deal with noise and non-uniform light. The wavelet transform approach then effectively restores all important aspects in all dimensions and dimensions by breaking the images down into the Low-Pass (LP) and High-Pass (HP) sub-bands. In order to efficiently capture smooth edges and textures, Different sides of the Convolutional Neuronal Network receive the HP sub-bands This is done through a process of Feature Recognition, Initial Segmentation, And Consistency Confirmation. Whereas the LP sub-bands are merged using local energy fusion, the energy information is recovered utilizing the averaging and selection mode. Qualitative evaluations, both subjective and objective, are used to support the proposed strategy. 12 field experts proved the effectiveness of the proposed methods based on precise details, visual contrasts, distortion in the reconstructed images, and no data redundancy using a customer specific example to make the subjective judgments.

2 citations

Journal ArticleDOI
TL;DR: Various image properties are studied and an Adaptive K-means Clustering method is applied for Fractal image with Entropy Properties and the results can be acceptable by the user since the grouping is made on the type of the image i.e., Good Visible, Moderate and Blur images.
Abstract: Image Enhancement is the method of improving the visibility of given image. Image Properties are used for the analysis of Quality of the given image. Various image Properties considered to improve the quality of the image. The Classification or grouping of images can be made by applying unsupervised image Classification algorithm. In our proposed method, various image properties are studied and an Adaptive K-means Clustering method is applied for Fractal image with Entropy Properties. The images are to enhanced on the basis of its grouping automatically. The resulted Classification can be acceptable by the user since the grouping is made on the type of the image i.e., Good Visible, Moderate and Blur images.

2 citations


Cited by
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Journal ArticleDOI
TL;DR: This paper presents a method for Offline Verification of signatures using a set of simple shape based geometric features that are Area, Center of gravity, Eccentricity, Kurtosis and Skewness, and results are discussed in the thesis.

78 citations

Proceedings ArticleDOI
28 Jun 2011
TL;DR: This paper presents the State-of-the-Art about offline signature verification system; this biometric identification method that had more attraction in recent years because of its necessity for use in daily life routines and when the signature needs to be immediately verified like bank checks.
Abstract: Biometrics can be classified into two types Behavioral (signature verification, keystroke dynamics, etc.) and Physiological (iris characteristics, fingerprint, etc.). Handwritten signature is one of the first few biometrics used even before computers. Signature verification is widely studied and discussed using two approaches. On-line approach and offline approach. Offline systems are more applicable and easy to use in comparison with on-line systems in many parts of the world however it is considered more difficult than on-line verification due to the lack of dynamic information. This paper presents the State-of-the-Art about offline signature verification system; this biometric identification method that had more attraction in recent years because of its necessity for use in daily life routines and when the signature needs to be immediately verified like bank checks. In this paper, we present signature forgery types, features types and recent methods used for features extraction in signature verification systems and approaches used for verification in signature systems. Then we discuss these approaches and for which type of forgeries its suitable. Finally, we suggest new interesting ideas to be incorporated in the future.

55 citations

Journal ArticleDOI
TL;DR: A new unsharp mask filtering technique with the combination of histogram equalization is used for the general-purpose images which maximizes the entropy of the image as well as controls the over and under enhancement by clipping the histogram of theimage.
Abstract: Contrast enhancement and Mean brightness conservation are two important parameters of image enhancement. A high contrast image is good in subjective quality assessment but also high contrast may cause over or under enhancement in the enhanced image. In this paper a new unsharp mask filtering technique with the combination of histogram equalization is used for the general-purpose images which maximizes the entropy of the image as well as controls the over and under enhancement by clipping the histogram of the image. After rigorous experimentation on standard data-set, it is observed that the information present in the image is highest in the proposed method i.e. the entropy value is highest and the mean brightness is also comparable with the other histogram based image enhancement methods. Mean opinion score(MOS) result shows that visual quality of the image is also better than existing methods.

51 citations

Journal Article
TL;DR: This letter has studied wavelet based approaches for image enhancement techniques based on discrete and stationary wavelet transforms with the interpolation algorithms, which will be used as resolution improvement and proposed an adaptive image enhancement algorithm based on image fusion.
Abstract: Satellite images are used in many fields of research. Resolution is the major issue in these kinds of images. In Image processing the image with higher resolution gives better results. In this letter we have studied wavelet based approaches for image enhancement techniques. These are based on discrete and stationary wavelet transforms with the interpolation algorithms, which will be used as resolution[1]improvement. Afterwards, compared the experimental results of both algorithms and we proposed an adaptive image enhancement algorithm based on image fusion. Compared the simulated results with the two methods and the proposed method shown that it gives improved PSNR.

34 citations

Journal Article
TL;DR: This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors.
Abstract: This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. In remote sensing, the image processing techniques can be categories in to four main processing stages: Image preprocessing, Enhancement, Transformation and Classification. Image pre-processing is the initial processing which deals with correcting radiometric distortions, atmospheric distortion and geometric distortions present in the raw image data. Enhancement techniques are applied to preprocessed data in order to effectively display the image for visual interpretation. It includes techniques to effectively distinguish surface features for visual interpretation. Transformation aims to identify particular feature of earth’s surface and classification is a process of grouping the pixels, that produces effective thematic map of particular land use and land cover.

25 citations