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This paper presents a face recognition method using the Weber Local Descriptor (WLD) feature. The WLD consists of differential excitation component and orientation component, which contains abundant local texture information. In our method, we firstly divide face images into a set of sub-regions and extract their WLD features respectively. We introduce the Sobel descriptor to obtain the orientation...
A motion-blur image has special blurred information which can be dealt to estimate its blurred direction. There are several methods to identify the direction such as based on directional derivation and weighted average [1]. The blurred image can't recognized smoothly and timely in the area of industrial machine vision. This paper provides an effective pretreatment method to indentify the motion-blur...
The performance of current state-of-the-art computer vision algorithms at image classification falls significantly short as compared to human abilities. To reduce this gap, it is important for the community to know what problems to solve, and not just how to solve them. Towards this goal, via the use of jumbled images, we strip apart two widely investigated aspects: local and global information in...
Recently, there has been tremendous interest in the area of mobile Augmented Reality (AR) with applications including navigation, social networking, gaming and education. Current generation mobile phones are equipped with camera, GPS and other sensors, e.g., magnetic compass, accelerometer, gyro in addition to having ever increasing computing/graphics capabilities and memory storage. Mobile AR applications...
Generic Fourier descriptor yield spectral features and have better retrieval performance due to multi-resolution analysis in both radial and circular directions of the shape. In the proposed work, an automated bamboo species recognition system based on shape features of bamboo culm sheath has been developed using Generic Fourier Moment and compare the result with Hu moment. The performance of the...
Biometric system provides more reliable and efficient means of identity verification. Gait recognition is the process of identifying a person by the way they walk. It is one kind of biometric technology that can be used to monitor people without their co-operation and has been receiving wide attention in the computer vision community. In this paper, we propose a new approach for extracting human gait...
The current OCR cannot segment words and characters from video images due to complex background as well as low resolution of video images. To have better accuracy, this paper presents a new gradient based method for words and character segmentation from text line of any orientation in video frames for recognition. We propose a Max-Min clustering concept to obtain text cluster from the normalized absolute...
This paper presents a method to extract cells from form documents of an unknown format based on intersection tracking and global optimization. Because of the increasing varieties of forms and complications in the forms, cell extraction has become a key factor in automatic form recognition. The proposed method produces cell candidates by using intersection features and tracing intersection points to...
With the increasing computational power of mobile devices and the increase in the usage of ordinary location-based services, the area of indoor location-based services is of growing interest. Nowadays indoor location-based services are used mainly for personalized information retrieval of maps and points of interest. Advanced location-based functionality often suffers from imprecise positioning methods...
Part-based recognition is expected to be robust in difficult handwritten character recognition tasks. This is because part-based recognition is based on aggregation of independent recognition results at individual local parts without considering their global relations and thus is robust against various deformations, such as partial occlusion, overlap, broken stroke, etc. Since part-based recognition...
Can a high-performance document image recognition system be built without detailed knowledge of the application? Having benefited from the statistical machine learning revolution of the last twenty years, our architectures rely less on hand-crafted special-case rules and more on models trained on labeled-sample data sets. But urgent questions remain. When we can't collect (and label) enough real training...
The discerning person usually can not read Braille information without training, then many parents have difficulty educating their blind or visually impaired children. Teachers engaged in special education have to depend on Braille translator when marking Braille papers or assignments, so subjective factors are brought into the evaluation process. This paper describes a new system that recognizes...
The experimental methods of psychology provides a basis of computer vision simulation, because it can reveal the law of human visual information processing. The shape and color are important features of stimulations, which are very crucial for the identification of stimulations. This study is based on the experimental psychology and BP neural networks, use experimental methods of reaction time measurements...
Image classification is a challenging research topic in image analyzing, and it is widely used in the area of image labelling and image semantic retrieval. In this paper, we first define a set of local semantic concepts to describe the local scene content, and then use the AdaBoost classifier to recognize the local semantics of the natural scene images. Furthermore, we propose three rules based on...
As orthogonal moments in the polar coordinate, radial orthogonal moments such as Zernike, pseudo-Zernike and orthogonal Fourier-Mellin moments have been successfully used in the field of pattern recognition. However, the scale and rotation invariant property of these moments has not been studied. In this paper, we present a generic approach based on Jacobi-Fourier moments for scale and rotation invariant...
Occlusion and "one sample per person" are two challenging problems for face recognition and still not well solved till now. This paper investigates the two problems and proposes a novel method based on sparse local features to solve them. The contribution of our work is three-fold: first, the key characteristics of successful applying SIFT features for face recognition are analyzed. Second,...
A layout recognition method for multi-page document image is proposed in this paper. Because there exists of spacings in vertical and horizontal direction in this kind of document, vertical and horizontal projection are used to extract the layout feature and Naive Bayes classifier is generated to realize the layout recognition of multi-page document. Experimental results show that the method of this...
Optical character recognition (OCR) is a popular research topic in artificial intelligent area. One of the most important parts of OCR is word recognition. So in this paper, we propose a combination method of selected subsets of Zernike features and MLP Back-Propagation Neural network to recognize Persian words. These words are the most useful and common words among 1000 words in Persian handwritings...
A novel and efficient method for face recognition with only one training image is proposed in this paper. It combines both texture feature and global topological information, and merges different features with proper weightiness. Firstly, we partition facial images according to “Three courtyards and five eyes” theory. Secondly, LBP is used to exact texture feature, and then we choose variance for...
Traditional window-based color indexing techniques have been widely used in image analysis and retrieval systems. In the existing approaches, all the image regions are treated with equal importance. However, some image areas carry more information about their content (e.g. the scene foreground). The human visual system bases indeed the categorization process on such set of perceptually salient region...
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