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Using spatio-temporal features is popular for action recognition. However, existing methods embed these local features into a global representation. Orders and correlations among local motions of each action are missing. This can make it difficult to distinguish closely related actions. This paper proposes a solution to address this challenge by encoding correlations of movements. Space-time interest...
Being one of the most effective video technologies, wireless capsule endoscopy (WCE) offers the physicians to diagnose the gastrointestinal (GI) diseases like ulcer non-invasively. Physicians, while analyzing the WCE videos, find it tedious to detect ulcer because of the huge amount of image frames present in WCE videos. This tedious reviewing process at times leads to inaccuracy in diagnosing ulcer...
This work presents the development of a system that performs the detection of boats from aerial images acquired by satellites. This will serve as a knowledge base for the implementation of a system to be implemented in a fleet of unmanned aerial vehicle. The main purpose of the system is to detect ships that are in the risk zone of rocket trajectory launched from Barreira do Inferno Launch Center...
Gender is one of the most useful facial attributes which are detected from human face images. In this work, we introduce a new gender classification system based on features extracted by Local Phase Quantization (LPQ) operators from intensity and Monogenic images. More detailed, the LPQ features are obtained from the input image (the intensity one) and from three other Monogenic components in the...
Brain tumor segmentation from magnetic resonance images is a critical step for early tumor diagnosis and treatment. However, accurate and general segmentation of brain tumor is still a challenging task due to complicated characteristics of brain tumor in magnetic resonance images. To solve this problem, we proposed a novel method for brain tumor segmentation based on features of separated local square...
This paper proposed a novel method to improve automatic age estimation from human faces. Three types of feature extraction algorithms are used, such as Extended Curvature Gabor Filter (ECG), Completed Local Binary Pattern (CLBP), and Local Directional Pattern (LDP). While the ECG is applied to the entire human face, CLBP and LDP are only applied to blocks with randomized scales, positions and orientations...
This paper describes FPGA implementation of object recognition processor for HDTV resolution 30 fps video using the Sparse FIND feature. Two-stage feature extraction processing by HOG and Sparse FIND, a highly parallel classification in the support vector machine (SVM), and a block-parallel processing for RAM access cycle reduction are proposed to perform a real time object recognition with enormous...
Video surveillance systems have enabled the monitoring of complex events in several places, such as airports, banks, streets, schools, industries, among others. Due to the massive amount of multimedia data acquired by video cameras, traditional visual inspection by human operators is a very tedious and time consuming task, whose performance is affected by fatigue and stress. A challenge is to develop...
Nowadays, merchandising is one of the significant method which allows to increase the sales. Therefore, activities such as monitoring the number of products on the shelves, completing the missing products and matching the planogram continuously have become important. An autonomous system is needed to automate operations such as product or brand recognition, stock tracking and planogram matching. In...
Recent development in micro-electronics technologies as well as the computer vision techniques increased demand to use Unmanned Aerial Vehicles (UAVs) in several industrial and civil applications. This paper proposed a vision based system, that is used in UAVs for search, rescue and transportation purposes. The proposed system is divided into two main parts: Vision-based object detection and classification,...
The current focus of our research is to detect and classify the plant disease in agricultural domain, by implementing image processing techniques. We aim to propose an innovative set of statistical texture features for classification of plant diseases images of leaves. The input images are taken by various mobile cameras. The Scale-invariant feature transform (SIFT) features used as texture feature...
This paper introduces a new system to identify handwritten signatures. For feature generation, we propose the Histogram of templates, while the Artificial Immune recognition System (AIRS) is used to achieve the identification task. A writer-independent strategy is proposed to train the AIRS to get an open system that can identify any new writer. Experiments are conducted on a benchmark dataset composed...
Interest on palmprint biometrics has experimented a strong growth in the last decades due to its useful characteristics as uniqueness, permanence, reliability, user-friendliness, acceptability, non-intrusiveness, and low cost of the acquisition devices, which make it attractive for civil and commercial applications. Accordingly, a wide research has been developed in this field. Nevertheless, there...
Speed limit traffic sign recognition plays a key role in intelligent transport system (ITS), especially in driver assistant system (DAS) and intelligent autonomous vehicles (IAV). Although traffic signs are clearly defined in color, shapes for easily detecting purpose, an excellent traffic sign detection system still be a challenge for researchers and manufactures because of the strict requirements...
This paper presents a multiple classifier system (MCS) to identify plants species based on the texture and shape features extracted from leaf images. A diverse pool of SVM and Neural Network classifiers is trained on four different feature sets, namely, Local Binary Pattern (LBP), Histogram of Gradients (HOG), Speed of Robust Features (SURF) and Zernike Moments (ZM). Then, a static classifier selection...
Insulator is an important component in the power grid. Therefore, faulty insulator can cause a great damage to the power grid that would lead to leakage currents flowing through line supports. This leads to increase in electrical loses, voltage drop and put human safety to risk. Hence, it is very important to monitor the condition of an insulator before resulting to a great damage in the power grid...
Realizing the automated and online detection of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding task. This research proposes a novel technique for detecting crowd abnormalities through analyzing the spatial and temporal features of the input video signals. This integrated solution defines an image descriptor that reflects the global motion information over...
This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After...
Pedestrian detection is a very important application of embedded real-time vision systems. It is essential in Advanced Driver Assistance Systems (ADAS) and Advanced Video Surveillance Systems (AVSS). The most widely used method involves a combination of Histogram of Oriented Gradients (HOG) features and Support Vector Machine (SVM) classifier. It offers quite high detection accuracy at the cost of...
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