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In this paper, we propose a fast and efficient method to extract skin and bone automatically. First, we smooth the images by applying anisotropic diffusion filter to remove noise. Then, the whole body is detected by using thresholding which is set automatically. In addition, we segment the contour of the skin by using morphological operators and connected component labeling (CCL). Finally, we extract...
For improving the accuracy of the traditional maximum entropy threshold segmentation algorithm, an improved maximum entropy segmentation algorithm is proposed. Firstly, it determines the possible range of an optimal segmentation threshold according to a simple statistical method, so as to reduce the interference of the background and magnify the proportion of the target region. Secondly, in a certain...
The Image segmentation is the focus in the image processing technology all the time. Medical image segmentation is an important application in the field of image segmentation. Wavelet transform is proposed to segment medical image. Firstly the gray level histogram of the medical image was processed using multiscale wavelet transform. Then the gray threshold was gradually emerged by the performance...
The traditional Fuzzy C-Means (FCM) clustering algorithm is usually based on the image intensity, so the segmentation results are unsatisfactory when the images are impacted by noise. Considering this shortcoming, in this paper the FCM objective function is improved by adding two kinds of spatial information: the relative position information and the intensity information of the neighborhood. Moreover,...
Granulation segmentation of the solar photosphere is important step to obtain correct morphometric measures. In this paper, we present a novel method, using morphological technique, for granules segmentation in the solar photosphere. Firstly, a morphological filtering, employing opening-by-reconstruction and closing-by-reconstruction, is used to eliminate image noise. Secondly, Otsu technique is implemented...
The handling of twist-locks has been a heavy burden for the container industry. To address this challenge, we are developing a customized mobile manipulator for handling the twist-locks. In this paper, we propose a fast normal computation algorithm for depth image, which is able to use normal deviation along eight directions to extract key points for segmenting points into objects on manipulation...
This paper proposes a novel license plate recognition method based on complex network to improve the accuracy of character recognition under the interference environment. An adaptive multi-threshold method based on the block separation and the feature lines of the image is proposed for the fast image binarization. Then the characters segmentation is performed using region labeling algorithm and the...
The most common problem in image processing is image segmentation. One of the methods which can segment an image with a high accuracy is Balloon Snake. It uses the energy minimization conception where it has a dynamic behavior that deforms from an initial position and converges to the boundary of the object in an image. However, we found that the accurateness always influences by the edge map detector...
Road detection is a basic functionality for driver assistance system such as vehicle and pedestrian detection. The main challenge is to deal with the presence of different objects (pedestrians and vehicles), the continuously varying background, different imaging conditions (different viewpoints, varying weather conditions and changing illumination), different road types (color, shape) and different...
This paper presents a method to automatic segmentation of cervical intraepithelial neoplasia (CIN3) parabasal cervical cells from PAP Smear images. The proposed method based on the structural characteristics of cervical; the region of nucleus by using Active Contour Model (ACM). The energy function is minimized in order to correct the less gradient of image energy area; to correct the cloudy contour...
In this paper, we proposed an unsupervised algorithm to identify the flooded areas from synthetic aperture radar (SAR) images based on texture information derived from the gray-level co-occurrence matrices (GLCM) texture analysis. Here, five GLCM features, namely, energy, contrast, homogeneity, correlation and entropy, are extracted from a SAR image. These features are input to an image segmentation...
Currently, the cytogenetic disorder such as the Down syndrome and the Prada william syndrome are a serious public health problem. The chromosome G-band images are applied for the automatic Karyotype analysis because it's easy to created and low cost. In contrast, the common problems of the chromosome images are disentangle such as the overlapping chromosome images. In this paper proposed a hybrid...
Brain disease is one of common diseases that threaten human health, which is becoming one of hot researches in society and medical profession. After a variety of image segmentation methods in the brain MR image segmentation are studied, it is found that FCM algorithm and SVM algorithm have a lot of advantages and good application prospection. Then a combination of unsupervised classification algorithm...
This paper studies the ceramic ring detection system in dynamic testing. The paper constructs CV motion detection model by dividing original window into child window. According to the maximum likelihood estimation of CV, the paper could judge the position of ceramic ring in the window with real-time, robustness, and accuracy.
The low-level line segment features have low accuracy as they are more easily affected by the noise and differeent line segment detectors. Furthermore, the line segment is not a good feature for matching across multiple views when we need to finish the 3D reconstruction. However, the line feature is more robust for the noise. In this paper, a kind of line feature, ideal line, is defined and optimally...
A vessel segmentation algorithm for pathological retina images is proposed. Firstly, the vessel centerlines are extracted by using the divergence of the normalized gradient vector field. Secondly, the main vessels are segmented by a sequence of bot-hat operators with different scales and directions. Thirdly, the skeleton lines of main vessels are generated after a skeletonization procedure. The distances...
In wireless network, the resource limitations and process speed are the main constraints. They make many traditional background subtraction methods unable to be applied in wireless network. Vibe algorithm is a newly proposed background subtraction technique and its computational load is very low. That makes it available in the wireless network. However, Vibe is a pixel-level algorithm and it does...
For the segmentation of ancient digitized document images, it has been shown that texture feature analysis is a consistent choice for meeting the need to segment a page layout under significant and various degradations. In addition, it has been proven that the texture-based approaches work effectively without hypothesis on the document structure, neither on the document model nor the typographical...
Scene text extraction, i.e., segmenting text pixels from background, is an important step before the text can be recognized. It is a challenging problem due to the cluttered background and the variation of lighting. In this paper, we propose a seed-based segmentation method that can automatically judge the text polarity, extract seed points of text and background, and segment texts by semi-supervised...
This paper describes a new approach for 3D LIDAR data segmentation in rough area. As 3D LIDARs become popular equipments in robotics, processing data in real time and safely driving on challenge environments are two important problems of intelligent vehicles. For overcoming roughness and unpredictable inclination in rough area, we design a graph-based segmentation framework. Each LIDAR scan line is...
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