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This paper presents a novel approach for recognition of unconstrained handwritten Marathi compound characters. The recognition is carried out using multistage feature extraction and classification scheme. The initial stages of feature extraction are based upon the structural features and the classification of the characters is done according to their parameters. The final stage of feature extraction...
Palmprint recognition inherently implements many of the same matching characteristics that have allowed fingerprint recognition to be one of the most well-known and best publicized biometrics. Because of palm region has obvious principle line features in outline and texture features in detail, in order to describe different patterns based on palmprint, a new feature extraction and match algorithm...
Automatic facial expression recognition is a challenging problem in computer vision, and has gained significant importance in applications of human-computer interaction. This paper presents a new appearance-based feature descriptor, the Local Directional Pattern Variance (LDPv), to represent facial components for human expression recognition. In contrast with LDP, the proposed LDPv introduces the...
This paper proposes a set of efficient algorithms for rotation- and scale-invariant texture classification. This set is based on the well established Gabor feature. A circular sum of the Gabor feature elements belonging to the same scale is proposed to reduce the effect of rotation, while a slide matching of augmented scales is proposed to address the effect of scaling. The resulting feature vector...
This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic...
Some target tracking occasions often requires to tracking a kind of target, such as human face, automobile and so on. A specific target tracking algorithm based on support vector machine (SVM) and AdaBoost is proposed. Moreover, the characteristic data of SVM is a critical factor to success to detecting target. The method selects part of Harr wavelet characters by AdaBoost as input data of SVM training...
This paper proposes a new ridgelet transform-based method to detect spoof fingerprint attacks in fingerprint biometric systems. It uses differences in textural characteristics observed in real and spoof fingerprints for spoof detection. Textural measures based on ridgelet energy signatures and ridgelet co-occurrence signatures are used to characterize fingerprint texture. Principal component analysis...
The paper proposes an on-line signature recognition algorithm with signature energy as feature. The signature energy features at sharp trajectory change points are extracted by means of Daubechies wavelet decomposition of signature signal. Then, 15 points with most dominant energies are chosen. Finally, a new algorithm of classification is put forward, after dynamic time warping matching, with computation...
This paper proposed a new steganalysis scheme of LSB-matching steganography based on statistical moments of the DFT of histogram of multi-level wavelet subbands. Before deriving these wavelet subbands a pre-processing apply to images under the test. The pre-processing contains removing some most significant bit planes. Then we decompose the image using three-level Haar discrete wavelet transform (DWT)...
The first step of any face processing system is detecting the location in images where faces are present. In this paper we present an upright frontal face detection system based on the multi-resolution analysis of the face. In this method firstly, skin-color information is used to detect skin pixels in color images; then, the skin-region blocks are decomposed into frequency sub-bands using contourlet...
This paper analyzes the palmprint textures with a multi-resolution method. Texture feature vectors of palmprint are extracted by wavelet transformation. With the texture feature, isodata clustering method is used to achieve classification of the Feature vectors. Based on the classification, euclidean distance within-class and between-class are calculated to match the feature. Experimental result illustrates...
In this paper, we investigate an approach to feature extraction for bank note classification by exploiting the potential of wavelet transform. In the proposed method, high spatial frequency coefficients taken from the wavelet domain are examined to extract features. We first perform edge detection on bill images to facilitate the wavelet feature extraction. The construction of feature vectors is then...
Fast image retrieval is the key to success for operations on large image databases, and a great many techniques have been developed for efficient retrieval. However, most of these methods are tailored to visual scenes or to images having limited variations. We investigate the searching of enormous databases (of up to 10/sup 7/ images) for the matching and identification of precious stones (principally...
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