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While Histograms of Gradients (HOG) has been proven as an excellent feature set for human detection, its intricate computation does not readily lend itself to be realized into high performance and economical hardware. This paper proposes several methods to simplify complicated computations of HOG, so that HOG feature extraction can be speeded up, which is essential in real-time applications, and become...
In this paper, we propose new data features to improve the off-line handwritten signature verification. The proposed features combine advantages of LBP and topological characteristics. Specifically, the Orthogonal Combination of LBP, which provides an LBP histogram with a reduced size, is combined with a topological descriptor that is called longest run features. The verification task is achieved...
Good performance of pedestrian detection in an automatic driving system is a necessary task. Many pedestrian detection algorithm use Histogram Oriented Gradient (HOG) for feature extraction and Support Vector Machine (SVM) for classification. Some papers use additional features with HOG, such as Local Binary Pattern (HOG-LBP), to improve the performance. Neural Network and Extreme Learning Machine...
In many applications such as dealing with database, continuous environment and humanoid robots, the machine often deals with large amount of data every day of work. Dealing with large amount of data requires fast as well as accurate learning algorithms to do the classification. A new supervised non parametric Partial Histogram Bayes learning algorithm (PHBayes) is proposed and presented in this paper...
This paper addresses two contributions for improving the accuracy and speed of preceding car detection systems. First, it proposes a feature description using Scalable Histogram of Oriented Gradient (SHOG) to solve scale problem of car region on the image. Without resizing the images to a fixed size, it is capable to extract a high-discriminated features with on the same feature space. Second, instead...
Human face based gender recognition is a challenging issue in image processing and machine vision domain. In this paper we proposed an approach for gender recognition using combination of statistical features and Local Binary Pattern (LBP). The optimal block size and statistical features set are determined by sequential forward floating selection (SFFS) algorithm for gender recognition improvement...
Spatial partitioning is proven to be beneficial for the tasks of image classification, scene categorization and object recognition. The most popular method to capture rough spatial structure of the scene is spatial pyramid matching. However, spatial pyramid matching results in an image representation that is sensitive to rotations. In this research we investigate the influence of upright and rotated...
According to the World Health Organization (WHO), as of 2012 esophageal cancer is the eighth-most common cancer globally with 456,000 new cases during the year. One of the triggers of the esophageal cancer is the hiatus hernia, and currently, the frequency disease increases with age, from 10% in patients younger than 40 years to 70% in patients older than 70 years old. Given the above, the aim of...
Sensory information, such as the tactile or proprioceptive signals, helps motor brain-machine interface (mBMI) work more naturally. Before applying sensory feedback, we need to explore if the neural activities are discriminative to different stimuli during a BMI task. Previous studies on the cortical discrimination are mainly focused on the rat whisker system. In this paper, we design a BMI task,...
In this paper, we present a real-time and energy-efficient multi-scale object detector using Histogram of Oriented Gradient (HOG) features and Support Vector Machine (SVM) classification. Parallel detectors with balanced workload are used to enable processing of multiple scales and increase the throughput such that voltage scaling can be applied to reduce energy consumption. Image pre-processing is...
License plate character segmentation (LPCS) is a very important part of vehicle license plate recognition (LPR) system. The accuracy of LPR system widely depends on two parts; namely license plate detection (LPD) and LPCS. Different country has different types and shapes of LPs are available. Based on character position on LP, we can find two types of LPs over the world, single row (SR) and double...
There are many social networking web sites used by people and number of photos is uploaded by them. But from photos it is difficult to predict the relationship among the people if necessary. So there is need of system for automatic identification and prediction of relationship among them, specifically kinship from photo. So, we proposed system, which uses Computer Vision, Face recognition, Feature...
The histogram specification turns a shape of a histogram into that we want to specify. This technique can be applied usefully in various image processing fields such as machine vision. However, the histogram specification technique has its basic limits. For instance, the histogram does not have location information of pixels. Also, the accuracy of specification drops because of quantization error...
This paper presents a new methodology for aligning three-dimensional (3D) models of objects, based on point correspondences. In this case, objects are modelled as 3D point clouds. The proposed methodology considers pairs of such point clouds and firstly down-samples them in order to further improve processing time. Then, corresponding points are allocated between the processed point clouds, by using...
This paper proposes a novel algorithm for Content Based Scene Retrieval (CBSR) using video features such as moment, histogram, Edge Histogram Descriptor (EHD)… This application is similar for Content Based Image Retrieval (CBIR) but instead of finding corresponding images in the database, it identifies the corresponding scene which contains the testing frame. The proposed algorithm can deal with scene...
In this paper, we propose a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of local...
Due to the increasing popularity of location-based services, the need for reliable and cost-effective indoor positioning methods is rising. As an alternative to radio-based localization methods, in 2011, we introduced MoVIPS (Mobile Visual Indoor Positioning System), which is based on the idea to extract visual feature points from a query image and compare them to those of previously collected geo-referenced...
The Bag of Words (BOW) method with spatio-temporal interest points has achieved great performance in human action recognition. However the traditional BOW methods based on vector quantization (VQ) suffer serious quantization error and lose masses of information. There are two main reasons leading these: the first is the codebook obtained by k-means has no obvious visual interpretation and second,...
Smile detection received a enormous attention due to its famous application as a ‘smile shutter’ in digital cameras. Edge Orientation Histograms (EOH) is one of the possible feature descriptors in a smile detector. This paper presents an evaluation of the use of Edge Orientation Histograms in a lip image based smile detector. The system built in this paper aims to discriminate lip images depicting...
We propose a method for detecting pedestrians in infrared images. The method combines a fast region of interest generator with fast feature pyramid object detection. Knowing the appearance model of pedestrians in infrared images we infer some edge and intensity based filters that generate the regions in which pedestrian hypotheses may appear. On those regions we apply the Aggregated Channel Features...
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