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Food photos are widely used in food logs for diet monitoring and in social networks to share social and gastronomic experiences. A large number of these images are taken in restaurants. Dish recognition in general is very challenging, due to different cuisines, cooking styles, and the intrinsic difficulty of modeling food from its visual appearance. However, contextual knowledge can be crucial to...
The main aim of recognising gestures is to build a system that can identify human gestures that are specific and then to use them to put forth desired information to the device. By using mathematical algorithms, human gestures can be interpreted. This is referred to as Gesture Recognition. Mudra is an expressive form of gesture that is mainly used in Indian classical dance form where the gesture is...
Palmprint is a unique and reliable biometric characteristic with high usability. Many works have been carried out on this field, during the past decades. Different algorithms and systems have been proposed and built successfully. Multispectral or hyperspectral palmprint imaging and recognition can be a potential solution to these systems because it can acquire more discriminative information for personal...
Trademark retrieval systems have been a well researched field however majority of these researches have been done on device trademarks and do not consider the presence of text embedded within trademark images as in case of composite marks. In this work a unified retrieval system has been proposed and implemented for composite trademarks. The technique is invariant to font size, font style and orientations,...
In recent years, there has been significant work in effective recognition of human facial expression. In this paper, we consider a new method for facial expression recognition, based on structural differences. The differences are regulated based on comprehensive laws for every expression. This article uses the Fuzzy Nero algorithm to classify support machines that have close fuzzy separation. With...
This paper proposes an entity recognition system in image documents recognized by OCR. The system is based on a graph matching technique and is guided by a database describing the entities in its records. The input of the system is a document which is labeled by the entity attributes. A first grouping of those labels based on a function score leads to a selected set of candidate entities. The entity...
The task of classifying videos of natural dynamic scenes into appropriate classes has gained a lot of attention in recent years. The problem especially becomes challenging when the camera used to capture the video is dynamic. In this paper, we analyse the performance of statistical aggregation (SA) techniques on various pre-trained convolutional neural network(CNN) models to address this problem....
Scene recognition is an important and challenging task in computer vision. We propose an end-to-end pipeline by combing convolutional neural networks (CNNs) with explicit attention model to determine several meaningful regions of original images for scene recognition. In the proposed pipeline, the spatial transformer network is leveraged as the attention module, which can automatically learn the scales...
Iris is one of the popular biometrics that is widely used for identity authentication. Different features have been used to perform iris recognition in the past. Most of them are based on hand-crafted features designed by biometrics experts. Due to tremendous success of deep learning in computer vision problems, there has been a lot of interest in applying features learned by convolutional neural...
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...
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