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Many studies of material property estimation and material recognition have been conducted. Previous approaches evaluate the validity or usefulness of hand-designed image features. Thus, we propose a method to directly and naturally acquire image features for material perception using convolutional neural networks. Using a fine-tuned network, we achieved approximately the same recognition accuracy...
The paper concerns accuracy of emotion recognition from facial expressions. As there are a couple of ready off-the-shelf solutions available in the market today, this study aims at practical evaluation of selected solutions in order to provide some insight into what potential buyers might expect. Two solutions were compared: FaceReader by Noldus and Xpress Engine by QuantumLab. The performed evaluation...
This paper presents a novel human ear recognition approach based on Multi-scale Local Binary Pattern (MLBP) descriptor to enhance the recognition performance. The proposed method includes the following two steps: (i) the feature extraction step that computes the MLBP descriptor-based features from human ear images, and (ii) the matching process that uses the Kullback Leibler (KL) distance to capture...
In this paper, a new sparse concept coding based image representation (SCCST) is proposed which efficiently extracts low dimensional features from the spatio-spectral decomposition of handwritten characters. The multiresolution decomposition is obtained by adopting an octave sampling based non-redundant S-transform. The introduction of sparsity not only reduces feature dimension significantly, but...
This paper addresses the problem of recognizing illogical object juxtaposing in the specific form of classifying digitized paintings in art movements. More precisely we distinguish between realism and surrealism movements. We propose a system based on feature extraction and machine learning that is able to understand the scene in the digitized paintings and to classify the art works from the two movements...
Reliable banknote recognition is critical for detecting counterfeit banknotes in ATMs and help visual impaired people. To solve this problem, it was implemented a computer vision system that can recognize multiple banknotes in different perspective views and scales, even when they are within cluttered environments in which the lighting conditions may vary considerably. The system is also able to recognize...
In this paper, we improve discriminative sparsity preserving projections (DSPP) which integrates global within-class structure into the discriminant manifold learning objective function for dimensionality reduction, and propose a new sparse subspace learning algorithm called improved discriminative sparsity preserving projections (IDSPP). Different from DSPP, IDSPP introduces between-class structure...
Accuracy and speed of face recognition frameworks are two foremost concerns for practical applications in recent researches. Linear regression classification (LRC) is a very famous and powerful approach for face recognition; however, it cannot perform very well under occlusion situations. In this paper, the regression parameters of the module-LRC are analyzed when a query facial image is partially...
In this paper, extraction of ship signatures from silhouette images of three-dimensional ship models and ship recognition from optical images are investigated. First of all, from the silhouette images of 3-dimensional ship models, with the help of feature vectors, ship signatures are created. Using three-dimensional ship models gets rid of the difficulty of obtaining real videos for the database and...
Nowadays, image processing is a widely accepted topic as it is used for multiple purposes. So as to do the image processing there are numbers of descriptors can be used for feature extraction. One of the main descriptor is Local binary pattern (LBP) which has different variants proposed by time and has become a popular approach in various applications. This paper presents a survey of modest LBP methodologies...
In any image, illumination is one of the challenges task and effect the performance of the system. In this paper, we have proposed new preprocessing approach to eliminate illumination effect from the human face images. In our approach we first apply Log transform on the input image to enhance illumination effect, output of this is given as input to the DoG filtering technique to smooth the image and...
Orientation, scale, sharp image transitions or singularities such as edges, and the other visual appearance are the major problem in texture classification. Texture classification is one of the most importantissue in image processing and computer vision. The applications of texture classification depends on classifying patterns or identifying objects in the field of image editing and completion, industrial...
In this paper, we propose a Palm print biometric recognition system based on scattering wavelet transform. First a novel approach for extracting Region of Interest (ROI) from palm image is presented. Then, a Scattering Wavelet Transform (SWT) is used to extract discriminative features from the input images that are useful to enhance correct matching. Then, a simple Euclidean distance based matching...
This paper presents the development of an Neural Network Based Skeleton Recognition and Sudoku Solving. The main objective of this work is to recognize the number and its corresponding position from a Sudoku image and also to solve any valid Sudoku. The recognition system is designed through an artificial neural network model. The neural network uses the mechanism of feedforwardbackpropogation technique...
This paper delivers a new database of iris images collected in visible light using a mobile phone's camera and presents results of experiments involving existing commercial and open-source iris recognition methods, namely: Iri-Core, VeriEye, MIRLIN and OSIRIS. Several important observations are made. First, we manage to show that after simple preprocessing, such images offer good visibility of iris...
As medicine, herbal plants have been widely used since ancient times, and are still used today. There are various types of herbal plants that can be used as medicine but due to the limited ability of communities to recognize the type of plants and the lack of information, both cause the limited use of plants as medicine. In this research, an herbal plants identification system based on leaves pattern...
Face quality assessment algorithms play an important role in improving face recognition accuracy and increasing computational efficiency of biometric systems. In the case of video analysis system, it is very common to acquire multiple face images of a single person. Strategy for optimally choose of the face images with the best quality from the set of images should base on special quality metric....
In this work, the problem of feature extraction and image recognition in the context of RGB images and depth information (RGB-D images) is addressed. The purpose of this paper is to study and compare some popular techniques for gender recognition in order to understand how much depth data improves the quality of recognition, and identify which combination between face descriptors and learning techniques...
Applications using face biometric are ubiquitous in various domains. We propose an efficient method using Discrete Wavelet Transform (DWT), Extended Directional Binary codes (EDBC), three matrix decompositions and Singular Value Decomposition (SVD) for face recognition. The combined effect of Schur, Hessenberg and QR matrix decompositions are utilized with existing algorithm. The discrimination power...
To improve the recognition performance of face recognition with single training sample, a face recognition algorithm based on fuzzy decision and maximum scatter difference with single training sample is proposed in this paper. With this method, each training sample is divided into several blocks to increase the number of elements in training sample set, on which the maximum scatter difference algorithm...
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