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It is important to choose a good hairstyle for women because it can enhance their beauty, personality, and confidence. One of the most important factors to consider for choosing the right hairstyle is the individuals face shape. An effective face shape classification can be used for constructing a hairstyle recommendation system. This paper presents a classification approach that divides face shapes...
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
Automatic recognition and interpretation of human emotions are becoming an integral part of intelligent products and services, which can lead to a breakthrough in domains such as healthcare, marketing, security, education and environment. This leads us towards Facial Expression Recognition (FER) systems, whose main objective is to detect an expressed emotion and recognize the same. The proposed work...
Comic books are considered a heritage in many countries. The colorful depiction of annotated events has gained an increasing amount of interest over the past decade as the digitization process took over printed media, in addition to the abundance and variety of available data. Several applications have been devised in the field of computer vision and natural language processing to handle comic book...
Traffic signs serve important functions on the road. Drivers can easily determine their directions and vehicle speeds by paying attention to traffic signs. However, it is only natural that sometimes drivers misjudge the position and meaning of traffic signs that they ignore them and in the worst case scenario, got involved in accidents. Therefore, technological improvements allow the development of...
Human segmentation is an important task in digital cameras. In this study, we present a framework of non-parametric human segmentation based on SVM. By exploiting spatial and color features of training images, the framework achieves noticeably better human segmentation results than GrabCut in terms of the overlap ratio with ground-truth.
The purpose of this study is to suggest the visual teaching method for the English vowel pronunciation, especially for the hearing-impaired who mostly rely on the visual aids, based on the SVM technique. By extracting phonetic features using the SVM technique from the sounds that are hard to hear by ear, the lip shapes for each vowel were refined. The lip shape refinement for vowels is advantageous...
Support Vector Machine (SVM) is a powerful classifier used widely in textual and web classification. It tries to find an hyperplane that separates positive and negative data, maximizes the margin. SVM is a classifier that is based on a kernel whose choice is very critical. We propose in this paper an implicit links based Gaussian kernel that uses an implicit links based distance. This kernel helps...
Gender classification using facial features has attracted researchers attention recently. Gender classification using texture features of faces exhibited promising improvement over other facial features. Gender classification finds applications in systems which use gender as one of the parameters. Local Binary Patterns (LBP) are known to have good texture representation properties. Through this paper...
This paper presents a design and implementation of the real-time traffic sign detection and recognition system based FriendlyARM Tiny4412 board. We develop an algorithm for detecting and recognizing the traffic signs in Vietnam with real-time processing capability and high accuracy. To achieve these objectives, we employ three main techniques consisting of traffic sign extraction based on chromatic...
Integrated video camera systems have been installed on fishing boats to trial for fishery monitoring in some countries. Currently, substantial amount of video footage is manually analyzed off the boats after each trip. Automatic processing of the videos is important for saving time and manpower. In this paper, an intelligent tuna recognition method is proposed. The method includes four steps. Firstly,...
Extraction of discriminate features which could represent the facial expression accurately plays a vital role in effective Facial Expression Recognition (FER). Although much progress has been made, selecting the discriminate features is still a challenging and interesting problem in the FER system. In this paper, we propose a new FER method, which uses the active shape mode (ASM) algorithm to landmark...
Alzheimer disease is a chronic neurodegenerative disease that usually starts slowly and gets worse over time. The diagnosis of Alzheimer's disease is often made very late. Several years pass after the start of the first manifestations before the diagnosis is made. According to many researchers, roll back 5 years to the start of the disease would reduce the frequency of 50%. In this work, we propose...
High resolution remote sensing imagery can provide more useful information, such as spectral, shape and texture information. However, traditional pixel-based image classification approaches may suffer the increase of within-class spectral variation with improved spatial resolution. This paper presents a novel method which combines the optimal segmentation scale with Bag-of-Visual Words (BOV) representation...
This paper presents a ℓ2,0-norm regularization based feature selection method to analyze very high resolution remote sensing imagery. The method tackles the feature selection problem based on a ℓ2,1-norm based objective function and a ℓ2, 0-norm equality constraint. The constrained optimization problem is solved by an efficient algorithm based on augmented Lagrangian method to figure out a stable...
Support Vector Machines (SVM) and Maximum Likelihood (MLLH) are the most popular remote sensing image classification approaches. In the past, SVM and MLLH have been tested and evaluated only as pixel-based image classifiers. Moving from pixel-based analysis to object-based analysis, a fuzzy classification concept is used through eCognition software [1]. In this paper, SVM and MLLH are separately adopted...
The development of robust object-oriented classification approaches suitable for medium to high spatial resolution satellite imagery provides a valid alternative to traditional pixel-based classification approaches. In the past, Support Vector Machines (SVM) have been tested and evaluated only as pixel-based image classifiers. Moving from pixel-based analysis to object-based analysis, a fuzzy classification...
In applications such as 3D face synthesis and animation, a prominent face landmark is required to enable 3D face normalization, pose correction, 3D face recognition and reconstruction. Due to variations in facial expressions, automatic 3D face landmark localization remains a challenge. Nose tip is one of the salient landmarks in a human face. In this paper, a novel nose tip localization technique...
In this paper, a small set of features based on local appearance and texture is applied to the task of image recognition and classification. These features are used to train and subsequently test three different machine learning techniques, namely k-Nearest Neighbors (K-NN), Support Vector Machines (SVM) and Ensemble Learning (Bagging). A case study on a publicly available object classification dataset...
Classifiers have known to be used in various fields of applications. However, the main problem usually found recently is about applying a classifier to large datasets. Thus, the process of reducing size of the training set becomes necessary especially to accelerate the processing time of the classifier. Concerning the problem, this paper proposes a new method which can reduce size of the training...
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