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Image classification is a general visual analysis task based on the image content coded by its representation. In this research, we proposed an image representation method that is based on the perceptual shape features and their spatial distributions. A natural language processing concept, N-gram, is adopted to generate a set of perceptual shape visual words for encoding image features. By combining...
We focus on feature extraction and selection to best represent texture and shape properties of plant diseases in an image-based leaf monitoring system implemented in a mobile-cloud environment. A number of textural and region-based features are aggregated from previous studies; also we introduce mean and peak indices of histogram-of-shape as disease property representations along with the proposed...
This paper proposes a novel Multiview Discriminative Analysis of Canonical Correlations (MDACC) for multiview learning. The proposed MDACC can capture discriminative features. Furthermore, we present a human action recognition framework by using MDACC to fuse multimodal features, which include the hierarchical Pyramid of Depth Motion Map (HP-DMM) for the depth images, the Histogram of Oriented Displacement...
This paper presents a novel local surface descriptor called rotational contour signatures (RCS) for 3D rigid objects. RCS comprises several signatures that characterize the 2D contour information derived from 3D-to-2D projection of the local surface. The inspiration of our encoding technique comes from that, viewing towards an object, its contour is an effective and robust cue for representing its...
We present a histogram-based real-time solution to detecting directly irradiated regions in digital fluoroscopic images. Our method leverages the power of model matching, machine learning and domain knowledge to characterize and segment images using histograms. The input image is automatically identified as containing partial, all, or null direct radiation. The regions with direct radiation are segmented...
Given the widespread availability of point cloud data from consumer depth sensors, 3D point cloud segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It benefits from the richer information contained in real world 3D data compared to 2D images. This also implies that the classical color segmentation challenges have shifted...
In modern days the demand for biometrics increases rapidly. The world still needs to solve many problems and answer to lot of questions regarding to biometrics for creating better solutions for recognition and verification of objects. Biometrics has become really important topic of our security. Number of input samples per person affects recognition in modern algorithms used for face recognition....
ShapeNets is an image representation, which is based on shape, compact structure, hierarchical image structure and appearance characteristic of object contour. In a ShapeNets, the shape of image is a window of containing objects which can be extracted with the method of objectness. The outline of objects can also be extracted in a line boundary detection algorithm based on histogram of gradients direction,...
In this paper, we propose a new local descriptor for action recognition in depth images. Our proposed descriptor jointly encodes the shape and motion cues using surface normals in 4D space of depth, time, spatial coordinates and higher-order partial derivatives of depth values along spatial coordinates. In a traditional Bag-of-words (BoW) approach, local descriptors extracted from a depth sequence...
Interaction experience in multimedia systems can be improved by adding personalization. Current applications for building and animating characters to represent real users are typically based on pose and motion detection. For so doing, computer vision algorithms do not exploit the anatomical characteristics of the human body for improving their classification accuracy. This work presents an strategy...
The purpose of this study is to create a software system to facilitate the organization of and searching for social images acquired from social sites on the Web (such as Facebook or Flikr), taking into account the images' features as well as user preferences. To achieve our goal, we design a solution based on image clustering, grouping together images sharing similar semantic and visual features,...
Detecting infrared pedestrian in outdoor smart video surveillance is always a challenging and difficult problem. Although there have been many methods based on histograms of oriented gradients (HOG) to solve this problem, they would probably fail because of shelter and poor quality of image. To overcome this problem, we propose a robust feature to describe pedestrian which is called entropy-edge weighted...
Content based image retrieval helps manipulators to retrieve pertinent images based on their contents. A consistent content-based feature extraction technique is required to meritoriously extract most of the information from the images. These important elements include color, texture, intensity or shape of the object inside image. Various descriptors required for extracting global and local features...
If the pre-processing phase, in optical character recognition systems, is the heart of the recognition process, the segmentation stage is the "aorta" of this heart. This paper introduce a reliable segmentation technique for Arabic handwritten script. Number of techniques like, script height, character width, pen thickness and word/subword gaps are used to design an efficient segmentation...
The field of medical image analysis has grown and these advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support. This paper presents a simple yet efficient image processing approach by proposing a new image feature detector...
This paper introduces a new eddy detection method based on object segmentation strategies. It incorporates the advantages of the Okubo-Weiss (OW) method, and improves the algorithm robustness by using three different segmentation methods. First, by intersecting the OW mask with the positive and negative SLA masks, two separate initial eddy candidate segment masks for anticyclonic and cyclonic eddies...
Vehicle detection and recognition from aerial imagery provides useful information for local vehicle volume estimation and traffic monitoring. In this paper, we propose a method that accurately detects vehicles in urban environment using a probabilistic classification method followed by a refinement based on object segments. Both classification and segmentation methods make use of coregistered aerial...
Indirect immunofluorescence (IIF) imaging is an important technique for detecting antinuclear antibodies in HEp-2 cells and therefore employed in the diagnosis of autoimmune diseases and other important pathological conditions involving the immune system. HEp-2 cells are often categorised into six groups (homogeneous, fine speckled, coarse speckled, nucleolar, cytoplasmic, and centromere cells), which...
This paper presents a system to recognize face by a variation of LBPH. We use a method of regression of local binary features to get the landmark of face image whose computational complexity is very low. We utilize these landmark points which can be trained to align the face, to extract the facial features. By calculating the Local Binary Patterns Histogram (LBPH) of these landmark points and its...
The paper mainly argues two questions, one is how to extract the feature of the ceramic productions based on the pairwise geometric histogram, and another is how to index and retrieval the ceramic productions. They are researched including the PGH-based shape coding, the prediction of the match cost, and the PGH-based retrieval. The PGH-based retrieval model of the ceramic productions is analyzed,...
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