The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes an effective method to scene recognition based on bags-of-words (BoW) algorithm. Current scene classification methods usually treat all the codewords equally important when using BoW histogram to represent an image. This assumption, however, does not comply with many real-world conditions as different codewords usually have different discriminating power when representing different...
This paper proposes a facial expression recognition system for the laughter therapy. The proposed system takes two steps: face detection and facial expression recognition. At the face detection stage, candidate facial areas are detected in real time from images taken by a camera in consideration of Haar-like features, followed by the application of a SVM(Support Vector Machine) classifier to detect...
Gray Scale Kernel has been recently introduced for image recognition tasks. The kernel is proved to be positive definite and thus can be used in Support Vector Machine (SVM) based recognition. In this paper, Profile Histogram Intersection (PHI) kernels, Detail Histogram Intersection (DHI) kernels and Susan Detail Histogram Intersection (SDHI) kernel function are proposed which based on traditional...
Accurate pedestrian recognition is required for practical applications such as automotive and security applications. To improve accuracy of recognition, accurate tracking is indispensable just as detection. The authors proposed a novel accurate tracking scheme using HOG features and its parallel implementation on GPU aiming real-time processing. However, the implementation does not have enough performance...
Recently, scene recognition is becoming an additional function in digital camera. Automatic scene understanding is a highest-level operation in computer vision, and it is a very difficult and largely unsolved problem. The conventional methods usually use global features (such as color histogram, texture, edge) for image representation and recognize scene types with some classifiers (such as Bayesian,...
Capsule endoscopy (CE) has gradually seen its wide application since it can directly view the small bowel in human body for the first time. However, a challenging problem is that too many images produced in each examination pose a tough workload to physicians. In this paper, we propose a new scheme aiming for intestinal polyp detection for CE images in order to partially solve this problem. This new...
In this paper, a three tier strategy is suggested to recognize the hand-printed characters of Devanagari script. In primary and secondary stage classification, the structural properties of the script are exploited to avoid classification error. The results of all the three stages are reported on two classifiers i.e. MLP and SVM and the results achieved with the later are very good. The performance...
This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next layer. In this way, instead of the normal linear combination of kernel activations, we can create non-linear...
A main challenge for texture analysis is to construct a compact texture descriptor which is not only highly discriminative to intra-class textures, but also robust to inter-class variations, geometric and photometric changes. In this paper, a new texture descriptor is developed by integrating the local affine-invariant texture features and the global viewpoint-invariant statistics. Based on the pixel...
The recognition of Chinese chess through computer vision includes chess detection and its character recognition, and the process should be fast and robust. In this paper, Robert operator is used to get the edge information of chess, then detection, localization and segmentation of the chess are realized through mathematical morphology and template circle method. A new algorithm based on projection...
It is important to protect children from harmful effects of objectionable materials, such as pornography, which are now prevalent on the Internet. In this paper, a new method from the feature porno-sounds recognition point of view is proposed to detect adult video sequences automatically which serves as a complementary approach to the recognition method from image's point of view. To the special of...
We propose a method that automatically estimates the degree of corrosion of galvanized steel of power transmission towers using digital images of the steel. Electric power companies have to determine the corrosion degree of steel for the maintenance of the towers. Accordingly, the technique to estimate the degradation degree of galvanization objectively and nondestructively is need. Our method is...
White blood cell (WBC) detection is one of the most basic and key steps in the automatic WBC recognition system. Its accuracy and stability greatly affect the recognition accuracy of the whole system. This paper presents a novel method for WBC detection based on boundary support vectors (BSVs). Firstly, v-Support Vector Regression (v-SVR) is introduced. Then sparse BSVs are obtained while fitting...
Image category recognition is important to access visual information on the level of objects and scene types. This paper combines different feature representations of images and learn a compact subspace of different features for the automatic recognition of object and scene classes. Compact visual-words and low-level-features object class subspaces are automatically learned from a set of training...
Pedestrian recognition on embedded systems is a challenging problem since accurate recognition requires extensive computation. To achieve real-time pedestrian recognition on embedded systems, we propose hardware architecture suitable for HOG feature extraction, which is a popular method for high-accuracy pedestrian recognition. To reduce computational complexity toward efficient hardware architecture,...
In this paper we present a new method for categorizing video sequences capturing different scene classes. This can be seen as a generalization of previous work on scene classification from single images. A scene is represented by a collection of 3D points with an appearance based codeword attached to each point. The cloud of points is recovered by using a robust SFM algorithm applied on the video...
Nowadays, pedestrian recognition for automotive and security applications that require accurate recognition in images taken from distant observation points is a recent challenging problem in the field of computer vision. To achieve accurate recognition, both detection and tracking must be precise. For detection, some excellent schemes suitable for pedestrian recognition from distant observation points...
In this paper, we investigated a new feature set, called the histograms of multi-scale orientations (H-MSO), for vehicle representation and detection. The multi-scale orientations on image pixels are calculated using Gabor filters of different scale and orientation parameters. Firstly, we divide the image into cells, and calculate the histograms of multi-scale orientations in each cell by statistics...
In this paper, we propose a method by engaging the one class support vector machine (OC-SVM) in the identification of diffractive optically variable images (DOVIs). OC-SVM, as a special SVM, can solve the problems of high-dimensional data sets and small sample size (SSS) with positive and negative unbalance training data. Image feature matrix is built by extracting image features from texture aspects...
Identifying the authenticity and integrity of digital images becomes increasingly important in digital forensics. In this paper, we focus on JPEG images and propose an effective method for detecting doctored images. We first investigate the statistical characteristics of DCT coefficients based on a recompression files sets, and analyze the differences of double compression effect between doctored...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.