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In this paper we consider how second order intensity features can be used to boost the accuracies of SVM-based pedestrian detectors, which remain much faster than recently popular deep learning approaches. In particular, we demonstrate that combining second order information features, corresponding to Hessians of patch-wise image intensities, with HOG and LBP features leads to more than 10% improvement...
This article presents our recent study on fusion of information at feature and classifier output levels for improved performance of offline handwritten Devanagari word recognition. We consider here two state-of-the-art features, viz., Directional Distance Distribution (DDD) and Gradient-Structural-Concavity (GSC) features along with multi-class SVM classifiers. Here, we study various combinations...
Number of mitotic cells in histopathology images of breast cancer is graded as one of three important factors for this cancer. In this paper, an automatic system is presented to assist pathologists in the diagnosis and mitotic cell counting in less time to overcome two major challenges in this context. The first challenge is the large variety in the structure of mitotic cells and the other is the...
In the article a vision system for shape and colour recognition of dishes (plates, bowls, mugs), which can be used to automate the process of customer service in a self-service canteen is described. In consists of three basic components: object segmentation using so-called background model subtraction, shape recognition using geometric invariant moments and SVM classifier, as well as colour recognition...
In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed...
Plants are fundamental for human beings, so it's very important to catalog and preserve all the plants species. Identifying an unknown plant species is not a simple task. Automatic image processing techniques based on leaves recognition can help to find the best features useful for plant representation and classification. Many methods present in literature use only a small and complex set of features,...
One of the methods that is often used to screening breast cancer is ultrasound examination but the result is very subjective. It depends on the ability the radiologist. Therefore, a tool that can help us to make it more objective needs to build. System on the device should be able to diagnose breast cancer malignancies of various parameters including the breast lesion shape parameter. Image classification...
Plant identification based on leaf is becoming one of the most interesting and a popular trend. Each leaf carries unique information that can be used in the identification of plants. In the identification of plants based on leaf, the leaf images needs to be pre-processed accordingly to extract the various critical features. In this paper, we present the identification of plants based on leaf features...
Sign language plays an important role in communication in hard-of-hearing community. Hand gesture recognition is an issue which is being researched widely. In this paper, we propose an approach, which can perform in real-time, to solve such problem for Vietnamese sign language. Instead of RGB data as many other solutions, the input of our system is depth images captured by Microsoft Kinect. We also...
Indirect immunofluorescence imaging is a fundamental technique for detecting antinuclear antibodies in HEp-2 cells and consequently important for the diagnosis of autoimmune diseases and other important pathological conditions involving the immune system. HEp-2 cells can be categorised into six groups: homogeneous, fine speckled, coarse speckled, nucleolar, cytoplasmic, and Centro mere cells, which...
This work presents a methodology for using Principal Component Analysis (PCA) and Genetic Programming (GP) for the classification of multi-class objects found in digital images. The image classification process is performed by using features extracted from images, through feature extraction algorithms, reduced by PCA and labeled by similarity comparing with other previously classified objects. GP...
The reading of ultrasound results is subjective, depending on the radiologist. Therefore, physicians need a tool as second opinion to make decision about the diagnosis of breast cancer malignancies depending on various parameters including shape parameter. To determine this parameter, a method to classify the lession's shape type of breast ultrasound image with image processing technique is proposed...
In modern industrial applications driven by Cyber-physical systems (CPS) it is a challenging task to model and optimize processes such as machine analysis and diagnosis. Since the CPS have to act autonomously, a procedure for automated decision making has to be designed. In our work we concentrate on the design of a decision procedure by a fuzzy classifier approach. For our application on decision...
In question answering system, the process of classifying a question to appropriate class and identification of the focus word play key role in determining accurate answer. In this paper, we propose an integrated pattern matching and machine learning approach for higher education domain that focuses on factoid question answering. We have developed a question taxonomy for higher education domain and...
At present, most of the existing seal image registration methods are based on shape, and most of the methods can't tolerate the image scale change. To overcome these problems, a general seal registration and identification approach is proposed in this paper. This method uses the classic scale invariant feature transform (SIFT) algorithm to extract the key points. To register the seal accurately, the...
Dynamic landslides are quality phenomena for the element offset of the world's range. Heavy rainfall and earthquake are the two primary attentiveness toward avalanches. The allocation of territory measurement is the most essential quantitative parameter of avalanches. Along these accumulations, the motivation behind this exploration is to clarify the achieved and spatial examination of precipitation...
Color represents an important attribute in the field of traffic sign recognition. However, when the color of the traffic sign fades or the traffic scene is collected in gray as in the case of Infrared imaging, then color based recognition systems fail. Other problems related to color are simply that different countries use different colors. Even within the European Union, colors of traffic signs are...
As falling is the most important issue that faces elderly people all over the world, this paper proposes a detection system for falling based on Machine Learning (ML). In the proposed system, a dataset of videos containing falling actions has been utilized via dividing each video into many shots that are consequently being converted into gray-level images. Then, for detecting the moving objects in...
Transformers are known as one of the most important equipment in power system transmission and distribution network. Safety of transformer insulation is determined mainly by its insulating oil dielectric strength. A major concern which threaten the withstand strength of a liquid insulation is the presence of particle contamination. One of the best methods to detect any abnormality and insulation weakness...
If a robot is expected to perform in the real-world, the robot should recognize objects in such environment using its multimodal sensors in real-time. Traditional multimodal object classification methods focus on recognizing known objects; however, it is impossible to learn all objects that we use. On the other hand, the classification of unknown objects has become a popular topic in image processing...
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