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This work proposes an off-line handwritten signature identification system using the Histogram of Symbolic Representation (HSR). The HSR is considered as one-class classifier which has the ability to generate a model for each writer using only its own reference signatures. This method allows also modeling the writing style of each writer by taking into account the variability of signatures. To evaluate...
Recent studies show that eyebrows can be used as a biometric or soft biometric for recognition. In some scenarios such as partially occluded or covered faces, they can be used for recognition. In this paper, we study eyebrow recognition using texture-based features. We apply features which have not been used before for eyebrow recognition such as 3-patch local binary pattern and WLD (Weber local descriptor)...
An Image Retrieval (IR) system is used for accessing and retrieving the images from large image database. Content means the image features like color, texture and shape of the image. For Color feature, it is scaling and rotation invariant. It encrypts the color data they are a good component to use under changing lighting conditions. Three color moments are figured per channel (e.g. 6 minutes if the...
Ear recognition Is still a standing problem In biometrics and has become an open research area in recent years. In this paper, we explore a new local feature extraction technique pyramid histogram of oriented gradients (PHOG) to represent ear images. However, the PHOG descriptor of the ear image is significantly large. To reduce the dimension of the PHOG descriptor, linear discriminant analysis (LDA)...
Handwritten character recognition has been emerging topic studied in the last half century and shape up to the level which is sufficient to develop a technology driven application. Now the rapidly increase in the computation power, CR creates an increasing demand for new emerging applications, which require more advanced methodologies. The problem of character segmentation and its recognition in India...
The description of vehicle appearance in Wide Area Motion Imagery (WAMI) data is challenging due to low resolution and renunciation of color. However, appearance information can effectively support multiple object tracking or queries in a real-time vehicle database. In this paper, we present a systematic evaluation of existing appearance descriptors that are applicable to low resolution vehicle reidentification...
Recently, there are increasing interests in inferring mirco-expression from facial image sequences. For micro-expression recognition, feature extraction is an important critical issue. In this paper, we proposes a novel framework based on a new spatiotemporal facial representation to analyze micro-expressions with subtle facial movement. Firstly, an integral projection method based on difference images...
Local ordinal signal relations, such as local binary or ternary patterns (LBP/LTPs) are invariant to frequent in practice spatially variant contrast/offset deviations that preserve image appearance. Our prior work extended this conventional LBP/LTP-based classifiers towards learning, rather than pre-scribing characteristic shapes, sizes, and numbers of such patterns. The learned LTPs showed more accurate...
3D Object recognition is one of the big problems in Computer Vision which has a direct impact in Robotics. There have been great advances in the last decade thanks to point cloud descriptors. These descriptors do very well at recognizing object instances in a wide variety of situations. Of great interest is also to know how descriptors perform in object classification tasks. With that idea in mind,...
Object tracking is one of the most important topics in computer vision. While the state-of-the-art tracking algorithms achieved great success, there are still some challenging problems to be solved. Firstly, it remains a tough task to develop a tracking algorithm with both accuracy and efficiency. Secondly, the ground truth is often given by a rectangular bounding box, which contains not only the...
In this paper, we propose to use Fourier descriptors (FD) for hand posture recognition in a vision-based approach. FD are widely used for shape representation and pattern recognition, they may also be well-adapted for hand posture recognition. The invariance properties of FD are discussed, and we provide a comparison of the performances with Hu moments. First, experiments are performed on the Triesch...
Facial expression recognition has many potential applications which has attracted the attention of researchers in the last decade. Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition. This paper represents an approach of combining the shape and appearance features to form a hybrid feature vector. We have extracted Pyramid...
In this paper we introduce a novel face representation method called Cross Local Binary Patterns(XLBP) to improve the robustness of face recognition for partially occluded and non-uniformly illuminated face images. In our method we use Radon transform to capture the coarse level shape information and XLBP to capture the texture information. Individual histograms computed on each sub-block of the face...
Core region detection of handwritten cursive words is an important step towards their automatic recognition. Several preprocessing operations such as height normalization, slant estimation etc. Are often based on this core region. This is particularly useful for word recognition of major Indian scripts, which have large character sets. The main parts of majority of these characters belong to the core...
This paper presents a flexible shape-based texture analysis method by investigating the co-occurrence patterns of shapes. More precisely, a texture image is represented by a tree of shapes, each of which is associated with several attributes. The modeling of texture is thus converted to characterize the tree of shapes. To this aim, we first learn a set of co-occurrence patterns of shapes from texture...
This paper considers the problem of script and nature identification at word level. We introduce Pyramid Histogram of Oriented Gradients (PHOG) features which have been employed successfully for discriminating between handwritten and machine-printed Arabic and Latin scripts. Most of the image features, used in previous identification system, are not effective to capture differences between these scripts...
Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image...
The local feature descriptor called SIFT, is one of the most widely used descriptors. The keypoints found with RSIFT and describe them in a standard way, which makes them invariant to the size changes, rotation, position, scale, and so on. These are quite powerful features and are used in a variety of tasks. This local feature SIFT descriptor gives potential key points, which are extracted from the...
In this work, we gathered some contributions to identify script and its nature. We successfully employed many features to distinguish between handwritten and machine-printed Arabic and Latin scripts at word level. Some of them are previously used in the literature, and the others are here proposed. The new proposed structural features are intrinsic to Arabic and Latin scripts. The performance of all...
In this paper a shape description for Arabic character recognition was presented. In the literature, shape description approaches are classified into either statistical or structural. In our work, we proceeded with a comparative study to compare the different shape descriptions using the same approaches and dataset of the Arabic characters. Our finds proved that the structural approach relying on...
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