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RISS 인기검색어
- 검색키워드
- 저자 : K. Rajakumar (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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MRI Image Retrieval Using Wavelet with Mahalanobis Distance Measurement
K. Rajakumar,S. Muttan 대한전기학회 2013 Journal of Electrical Engineering & Technology Vol.8 No.5
In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and H* elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.
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MRI Image Retrieval Using Wavelet with Mahalanobis Distance Measurement
Rajakumar, K.,Muttan, S. The Korean Institute of Electrical Engineers 2013 Journal of Electrical Engineering & Technology Vol.8 No.5
In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.
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Hyperspectral Image Classification using EfficientNet-B4 with Search and Rescue Operation Algorithm
S.Srinivasan,K.Rajakumar International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.12
In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.
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Ramya A.,Vijayakumar V. N.,Rajakumar K.,Balasubramanian V.,Balamuralikrishnan S. 한국물리학회 2020 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.77 No.12
A new class of intermolecular hydrogen bonded liquid-crystal complex (HBLC) was designed and synthesized from non-mesogenic benzylmalonic acid (BMA) and mesogenic 4n-pentyloxybenzoic acid (5OBA). Intermolecular hydrogen bonds (H-bond) and vibrational functional groups were characterized by using Fourier transform-infrared spectroscopy (FTIR). Textural characterizations and the corresponding transition temperature along with enthalpy values were observed using polarizing optical microscopy (POM) and differential scanning calorimetry (DSC). The optical absorption and emission bandgap energies were calculated by using ultraviolet-visible (UV-vis) and photoluminescence (PL) spectra. The phase transition temperature, thermal stability factor, and thermal span width were calculated and their impact on the liquid crystal properties are discussed. An interesting feature of the BMA+5OBA HBLC complex was the observation of schlieren textures, and the induced thermoluminescence with parachromic variation in the nematic phase is an alternative tool for the manufacture of opto-electronic devices.
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