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The following topics are dealt with : hidden Markov model; support vector machines; microarray sample classification; automated knowledge engineering; medical image edge enhancement; recurrent fuzzy multilayer perceptron; self organizing maps; data mining; business intelligence tool; context ontology driven relevant search; Web search result optimization; image compression analysis; natural feature...
The problem of vehicle extraction using airborne laser scanning (ALS) is studied under the framework of object-based point cloud analysis (OBPA). Object extraction relies on the partitioning of raw ALS data into various segments approximating semantic entities followed by classification. A 3D segmentation method working directly on point cloud is used, which features the detection of local arbitrary...
The paper realizes water body extraction well using object-oriented classification method based on SPOT5 image. Firstly, segment image according to multi-scale image segmentation method based on edge-detection algorithm. Secondly, determine various characteristic parameters in land surface features according to object characteristics such as spectrum, shape and texture. And thirdly, use SVM (Support...
In this paper, a work on representing plastic bottle shape using erosion based approach for an automated classification is reported. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This work will compare two versions...
Text detection in images is important for the retrieval of text information from digital graph, video databases and web sites. In this paper, a text detection method based on sparse representation classification with discrimination dictionaries is presented, which can detect text with different sizes, fonts and colors. The propose method detects edge information using Sobel operator and a sliding...
Detection of text from documents in which text is embedded in complex colored document images is a very challenging problem. There are a lot of potential uses of text extraction in image searching, archiving documents etc. In this paper, we propose a simple edge based feature to perform this task. It aims at detecting textual regions from the document and separating it from the graphics portion. The...
Cell enumeration in peripheral blood smears and cell are widely applied in biological and pathological practice. Not every area in the smear is appropriate for enumeration due to severe cell clumping or sparseness arising from smear preparation. The automatic selection of good areas for cell enumeration can reduce manual labor and provide objective and consistent results. However, this has been infrequently...
Facial expressions are the facial changes in response to a person's internal emotional states, intentions or social communications. In this paper, we fulfill the recognition of facial action units, i.e., the subtle change of facial expressions, and emotion-specified expressions. Our automatic facial expression analysis system includes face detection, facial component extraction, tracking and representation,...
There are many approaches to pedestrian detection in collision avoidance systems depending on the sensors (visible light, thermal infrared, radar, laser scanner) used for acquiring the data and the features (depth, shape, motion) used for detection. In this paper we present a method for shape based pedestrian detection in traffic scenes using a stereo vision system for acquiring the image frames and...
Histogram-based techniques are useful for image enhancement. However, these techniques often fail to produce satisfactory results for some low-contrast images. In this paper, we propose a new form of histogram for image contrast enhancement. The input image is first divided into several equal-sized regions according to the intensities of the gradients, their corresponding statistical values of gray...
This paper presents a novel approach to recognize similar handwritten numerals based on empirical mode decomposition (EMD). We firstly use the local maximum modulus of wavelet transform (MMWT) to get the width-invariant and grey-level invariant characterization of contours in an image. Then we apply EMD analysis to decompose the synthetic shift normalization of curvature into their components, which...
Algorithm design of iris outer edge location is one of keys in iris recognition. It dose ask for an excellent performance as well as an acceptable running time. Low-level technologies and simple classifiers are employed in this paper to meet these needs. First of all, we propose a gradient computation for point detection to ensure a shorter running time. In this part, points can be located as many...
Wireless capsule endoscopy (CE) is increasing being used to assess several gastrointestinal(GI) diseases and disorders. Current clinical methods are based on subjective evaluation of images. In this paper, we develop a method for ranking lesions appearing in CE images. This ranking is based on pairwise comparisons among representative images supplied by an expert. With such sparse pairwise rank information...
We present a novel classification scheme which uses partial object information that is selected adaptively using modified distance transform and represented as moment invariants (Hu moments) to compensate for scale, translation and rotational transformation(s). The moment invariants of different parts of an object are learned using AdaBoost algorithm [1]. The classifier obtained using the proposed...
This paper presents a novel multiscale classification likelihood (MCL) estimation method using hierarchical wavelet-domain hidden Markov tree(WDHMT) model. The key idea is that with inter-scale communication and intra-scale interaction of the WDHMT model, we can capture hierarchical classification information of the pixels at the vicinity of the weak boundary. Our framework consists of the following...
Detecting and segmenting out the regions of interest (ROIs) is one of the foundations in image processing and analysis. Because the final information sink of images is human, for segmenting out the ROIs effectively, we need to study human visual system (HVS) and imitate the behaviors when human viewing a scene. Researchers have found several factors which affect human attentions by studying eye movements...
The edge detection of the images is so important for image processing. There are different methods for improving edge detection. In the present work, a neural networks based system for edge extraction of Chinese winespsila micrographs is presented. Back propagation neural network (BPNN) with an improved activation function employing four adjustable parameters is used. Multi-scale mathematical morphological...
In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
This paper proposes an automatic approach to segmentation and asymmetry analysis for breast in infrared images. Hough transform, canny edge detection operator and other technologies are used to extract four feature curves that can uniquely separate the left and right breasts. These feature curves include the two parabolic curves describing the lower boundaries of the breasts, and the left and right...
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