no code implementations • 17 Feb 2024 • Asish Bera, Debotosh Bhattacharjee, Mita Nasipuri
Biometric is a better solution to win over the problems encountered by digital forensics.
no code implementations • 16 Dec 2023 • Asish Bera, Debotosh Bhattacharjee, Mita Nasipuri
The best identification accuracy of 98. 67%, and equal error rate (EER) of 4. 6% have been achieved using the subset of 25 features which are selected by the rank-based local FoBa algorithm.
no code implementations • 3 Aug 2023 • Asish Bera, Debotosh Bhattacharjee, Mita Nasipuri
Fine-grained image classification (FGIC) is a challenging task in computer vision for due to small visual differences among inter-subcategories, but, large intra-class variations.
no code implementations • 1 Aug 2023 • Asish Bera, Mita Nasipuri, Ondrej Krejcar, Debotosh Bhattacharjee
The proposed SYD-Net has achieved state-of-the-art accuracy on Yoga-82 using five base CNNs.
1 code implementation • 30 Jul 2023 • Debesh Jha, Vanshali Sharma, Debapriya Banik, Debayan Bhattacharya, Kaushiki Roy, Steven A. Hicks, Nikhil Kumar Tomar, Vajira Thambawita, Adrian Krenzer, Ge-Peng Ji, Sahadev Poudel, George Batchkala, Saruar Alam, Awadelrahman M. A. Ahmed, Quoc-Huy Trinh, Zeshan Khan, Tien-Phat Nguyen, Shruti Shrestha, Sabari Nathan, Jeonghwan Gwak, Ritika K. Jha, Zheyuan Zhang, Alexander Schlaefer, Debotosh Bhattacharjee, M. K. Bhuyan, Pradip K. Das, Deng-Ping Fan, Sravanthi Parsa, Sharib Ali, Michael A. Riegler, Pål Halvorsen, Thomas de Lange, Ulas Bagci
Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps.
no code implementations • 22 Oct 2021 • Asish Bera, Ratnadeep Dey, Debotosh Bhattacharjee, Mita Nasipuri, Hubert P. H. Shum
A presentation attack detection approach is addressed by assessing the visual quality of genuine and fake hand images.
no code implementations • 15 Oct 2015 • Satyabrata Maity, Debotosh Bhattacharjee, Amlan Chakrabarti
In this paper, a novel human action recognition technique from video is presented.
no code implementations • 16 Aug 2014 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri
Features are extracted from the reconstructed non-occluded face images in the form of face normals.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
In this paper, we present a novel Gabor wavelet based Kernel Entropy Component Analysis (KECA) method by integrating the Gabor wavelet transformation (GWT) of facial images with the KECA method for enhanced face recognition performance.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
Unlike the traditional zigzag scanning method for feature extraction a continuous scanning method from top-left corner to right then top-down and right to left and so on until right-bottom of the image i. e. a spiral scanning technique has been proposed for better feature selection.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
Firstly, the new morphological features i. e., features based on number of runs of pixels in four directions (N, NE, E, NW) are extracted, together with the GLCM based statistical features and LDP features that are less sensitive to the noise and non-monotonic illumination changes, are extracted from the significant blocks of the gradient image.
no code implementations • 5 Dec 2013 • Sourav Pramanik, Debotosh Bhattacharjee
In this system, first the facial features/components from training images are extracted, then ratios of length, width, and area etc.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
Secondly, the nonlinear discriminating features are analyzed and extracted from the selected low-energized blocks by the generalized Kernel Discriminative Common Vector (KDCV) method.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
This paper exploits the feature extraction capabilities of the discrete cosine transform (DCT) together with an illumination normalization approach in the logarithm domain that increase its robustness to variations in facial geometry and illumination.
no code implementations • 5 Dec 2013 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
Finally the best fitted Hough peaks are extracted from the Hough transformed significant blocks for efficient face recognition.
no code implementations • 5 Dec 2013 • Sourav Pramanik, Debotosh Bhattacharjee
An image fusion method based on salient features is proposed in this paper.
no code implementations • 3 Dec 2013 • Pramit Ghosh, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
The analysis and counting of blood cells in a microscope image can provide useful information concerning to the health of a person.
no code implementations • 3 Dec 2013 • Pramit Ghosh, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
The objective of this work is to automate the blood related pathological investigation process.
no code implementations • 18 Sep 2013 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
In this present smoothing technique we have built the neighborhood surrounding a particular point in 3D face and replaced that with the weighted value of the surrounding points in 3D face image.
no code implementations • 18 Sep 2013 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
In this paper we present a novel method that combines a HK curvature-based approach for three-dimensional (3D) face detection in different poses (X-axis, Y-axis and Z-axis).
no code implementations • 18 Sep 2013 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
In this paper, we propose a new approach that takes as input a 3D face image across X, Y and Z axes as well as both Y and X axes and gives output as its pose i. e. it tells whether the face is oriented with respect the X, Y or Z axes or is it oriented across multiple axes with angles of rotation up to 42 degree.
no code implementations • 13 Sep 2013 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri, Dipak kr. Basu
In this paper we present a novel technique of registering 3D images across pose.
no code implementations • 13 Sep 2013 • Parama Bagchi, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
All the experiments have been performed on the FRAV3D Database.
no code implementations • 4 Sep 2013 • Ayan Seal, Mita Nasipuri, Debotosh Bhattacharjee, Dipak Kumar Basu
A distribution of blood vessels are unique for each person and as a set of extracted minutiae points from a blood perfusion data of a human face should be unique for that face.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak kr. Basu
Image processing methods are used to pre-process the captured thermogram, from which different physiological features based on blood perfusion data are extracted.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
Secondly face features are extracted from the croped region, which will be taken as the input of the back propagation feed forward neural network in the third step and classification and recognition is carried out.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak kr. Basu
Therefore this paper describes an efficient approach of human face recognition based on wavelet transform from thermal IR images.
no code implementations • 4 Sep 2013 • Ayan Seal, Suranjan Ganguly, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu
In the first approach, the training images and the test images are processed with Haar wavelet transform and the LL band and the average of LH/HL/HH bands sub-images are created for each face image.
no code implementations • 17 Jun 2011 • Arindam Kar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, Mahantapas Kundu
In this paper, we present a technique by which high-intensity feature vectors extracted from the Gabor wavelet transformation of frontal face images, is combined together with Independent Component Analysis (ICA) for enhanced face recognition.
no code implementations • 17 Jun 2011 • Mrinal Kanti Bhowmik, Gautam Majumdar, Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri
This paper demonstrates two different fusion techniques at two different levels of a human face recognition process.
no code implementations • 5 Jul 2010 • M. K. Bhowmik, Debotosh Bhattacharjee, M. Nasipuri, D. K. Basu, M. Kundu
Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks.
no code implementations • 5 Jul 2010 • Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
The main advantage of using wavelet transform is that it is well-suited to manage different image resolution and allows the image decomposition in different kinds of coefficients, while preserving the image information.
no code implementations • 5 Jul 2010 • M. K. Bhowmik, Debotosh Bhattacharjee, M. Nasipuri, D. K. Basu, M. Kundu
Here, coefficients of discrete wavelet transforms from both visual and thermal images are computed separately and combined.
no code implementations • 5 Jul 2010 • Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
In this paper we present a technique for fusion of optical and thermal face images based on image pixel fusion approach.
no code implementations • 5 Jul 2010 • Santanu Halder, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
This paper aims at determining the characteristics of a face image by extracting its components.
no code implementations • 5 Jul 2010 • Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
This paper investigates the multiresolution level-1 and level-2 Quotient based Fusion of thermal and visual images.
no code implementations • 5 Jul 2010 • Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
Here, we have used thermal face images as those are capable to minimize the affect of illumination changes and occlusion due to moustache, beards, adornments etc.
no code implementations • 5 Jul 2010 • M. K. Bhowmik, Debotosh Bhattacharjee, M. Nasipuri, D. K. Basu, M. Kundu
In this method fused images are generated using visual and thermal face images in the first step.
no code implementations • 21 May 2010 • Mrinal Kanti Bhowmik, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
This paper presents a novel approach to handle the challenges of face recognition.
no code implementations • 21 May 2010 • Santanu Halder, Debotosh Bhattacharjee, Mita Nasipuri, Dipak Kumar Basu, Mahantapas Kundu
This paper aims at generating a new face based on the human like description using a new concept.
no code implementations • 21 May 2010 • Debotosh Bhattacharjee, Dipak Kumar Basu, Mita Nasipuri, M. Kundu
To reduce further we have applied feature selection method to select indispensable features, which will remain in the final feature vectors.