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The aim of this paper is to develop a system that involves character recognition of Brahmi, Grantha and Vattezuthu characters from palm manuscripts of historical Tamil ancient documents, analyzed the text and machine translated the present Tamil digital text format. Though many researchers have implemented various algorithms and techniques for character recognition in different languages, ancient...
In this paper, a facial expression recognition algorithm based on Gabor and conditional random fields is proposed. Firstly, owing to the fact that in the existing databases, the number of people and images are relatively small, we established our own facial expression database, and some preprocessing methods are performed thereon. Secondly, Gabor features are extracted in five scales and eight directions...
In this paper, we propose an improved face recognition approach based on the combination of Vector Quantization (VQ) and Markov Stationary Feature (MSF) which obtain the extended MSF-VQ features from facial sub-regions for face recognition. It can not only utilize the MSF framework to extend the VQ histogram based features with the spatial structure information but can also incorporate more location...
Subspace learning plays a key role in pattern recognition and machine learning. However, its performance would be degraded when data are corrupted by various occlusions. Low-rank representation (LRR) can recover the corrupted data and explore low-dimensional subspace structures embedded in data. Inspired by low-rank representation and subspace learning, in this paper, we propose a regularized low-rank...
The paper presents a thorough evaluation of two representative visual place recognition algorithms that can be applied to the problem of indoor localization of a person equipped with a modern smartphone. The evaluation focuses on comparing two different state-of-the-art approaches: single image-based place recognition, represented by the FAB-MAP algorithm, and recognition based on a sequence of images,...
On the basis of explaining the principles of wavelet transform, neural network, and wavelet neural network, the paper examines two methods of face recognition: one is based on neural network, the other is based on wavelet neural network. The paper also offers the features and differences based on algorithmic simulation. The result of the stimulation reveals that face recognition using wavelet neural...
The ROI (region of interest) extraction is the key step in palmprint or palm vein recognition, which is very important for the subsequent feature extraction and recognition. In this paper, the ROI extraction method for palmprint and palm vein recognition is mainly studied. Firstly, the preprocessing operation of palmprint and palm vein is carried out by using binary and morphological denoising technology,...
In this paper, we present a system to recognize text in traffic signs, along with its context based recognition result corrections that we developed. This system detects text in traffic signs region using contour detection and using KNN Classifier to recognize letters in it. The result of the recognitions that may contain errors will be corrected using Forward Reverse Dictionary that has Contextual...
In recent years, we can observe an increasing use of biometric technology in our daily lives. Face recognition has several advantages over other biometric modalities, since that it is natural, nonintrusive, and it is a task that humans perform routinely and effortlessly. Following a recent trend in this research field, this paper focuses on a part-based face recognition, exploring and evaluating specific...
The performance of printed document recognition has been significantly improved by generating synthetic images to augment the training data, particularly by providing more variability in the linguistic contents. Handwriting recognition benefits less from this data augmentation and the only variability that is usually added is via artificially generated combinations of skew, slant and noise. Generating...
We experiment with off-line recognition of handwritten flowcharts based on strokes reconstruction and our state-of-the-art on-line diagram recognizer. A simple baseline algorithm for strokes reconstruction is presented and necessary modifications of the original recognizer are identified. We achieve very promising results on a flowcharts database created as an extension of our previously published...
Periocular recognition has gained significant importance with the increasing use of surgical masks to safeguard against environmental pollution or for improving accuracy of iris recognition. This paper proposes a new framework for accurately matching cross-spectral periocular images using Markov random fields (MRF) and three patch local binary patterns (TPLBP). We study the problem of cross-spectral...
This paper attempts to recognize online Farsi handwriting using the freeman chain codes and hidden Markov model. Chain codes reduce the number of data with using the direction of breaks and keeping the direction of pen movement. Hence, it can be used as an effective way to recognition of online sub-words. After breaking the sub-word into component parts (main body and strokes), each part separately...
Traditional AR frameworks for gaming and advertising focus on tracking 2D static targets. This limits the plausible use of this solutions to certain application cases like brochures or posters, but deprives their use for dynamically changing 2D targets, such as video walls or electronic billboards used in advertising.In this demo, we show how to use a rapid, fully mobile image recognition system to...
Current research in iris recognition is moving towards enabling more relaxed acquisition conditions. This has effects on the quality of acquired images, with low resolution being a predominant issue. Here, we evaluate a superresolution algorithm used to reconstruct iris images based on Eigen-transformation of local image patches. Each patch is reconstructed separately, allowing better quality of enhanced...
In order to further improve the recognition rate and computing efficiency of modular 2DPCA in face recognition, an improved modular 2DPCA method based on image segmentation is proposed. Firstly, segmentation of threshold value optimization is utilized to segment face image of training samples into several non-overlapping sub-image spaces so that the pixel number has uniform distribution in each sub-image...
Face alignment is very crucial to the task of face attributes recognition. The performance of face attributes recognition would notably degrade if the fiducial points of the original face images are not precisely detected due to large lighting, pose and occlusion variations. In order to alleviate this problem, we propose a spatial transform based deep CNNs to improve the performance of face attributes...
In this paper, we proposed a new algorithm based on independent keypoints databases for indoor place recognition. In analogy with set operation, a new kind of operations for keypoints sets are defined to describe the process of independent keypoints database establishment and place classification. To obtain the databases, keypoints are firstly extracted from sample images whose class are known, and...
In our current tourism system, whenever a tourist visits a monument or a famous spot, to know more about the place, he/she hires a guide. With the advancement in the technology, the role of the guide is being taken up by the different services and applications. The increase in the use of mobile phones has made it easier to provide different applications available to the tourists ‘on the go’. In this...
In big data era, digital information is growing rapidly. False and unlawful images influence our normal work and life, especially the exaggerated or fake propaganda of electronic commerce merchants. In this article, our purpose is to help people find out fake qualification certificate information automatically. Base on collecting and classifying web images, we apply Convolutional Neural Network (CNN)...
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