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Hand segmentation is often the first step in applications such as gesture recognition, hand tracking and recognition. We propose a new technique for hand segmentation of color images using adaptive skin color model. Our method captures pixel values of a person's hand and converts them into YCbCr color space. The technique will then map the CbCr color space to CbCr plane to construct a clustered region...
In this paper, robust descriptors are extracted to detect video copies generated by complicated transformations. The main contribution of the proposed method lies in three aspects. Firstly, the complicated transformations on video copies are identified and tackled to guarantee the extraction of robust descriptors. Secondly, a motion classification approach is proposed to divide the video into video...
Object recognition systems need effective image descriptors to obtain good performance levels. Currently, the most widely used image descriptor is the SIFT descriptor that computes histograms of orientation gradients around points in an image. A possible problem of this approach is that the number of features becomes very large when a dense grid is used where the histograms are computed and combined...
Microcalcifications are one of the key symptoms facilitating early detection of breast cancer. In this paper, The textural features are extracted from the segmented mammogram image to classify the microcalcifications into benign, malignant or normal. The reduced features are selected from the extracted set of features using reduction algorithms. Initially the reduced features are normalized between...
Intravascular ultrasound can provide clear real-time cross-sectional images, including lumen and plaque. In practice, to identify the plaques tissues in different pathological changes is very important. However, the grayscale differences of them are not so apparent. In this paper a new textural characteristic space vector was formed by the combination of Co-occurrence Matrix and fraction methods....
In laparoscopic surgery, surgeons often encounter paradoxical vision according to their position against the camera position. Such a paradoxical vision evokes confusion and surely deteriorates surgical performance. Previous researches indicated inverted mirror image is useful to compensate this problem though upside-down inversion makes depth sensation perplex. To solve the dilemma, we proposed modified...
This paper presents a novel architecture for a classification system based on the visual saliency of images. The work is motivated by the difficulty of reviewing large numbers of images as a human operator in the context of Autonomous Underwater Vehicle (AUV) surveys. We formulate a feature space in which an algorithm operates over color and texture to determine saliency and illustrate how this can...
For any autonomous system it is very important to acquire the knowledge of the surrounding environment. Images and videos acquired by the vision based sensors can provide meaningful information about the environment, which can be very useful for the navigation of autonomous system like mobile robots. To extract road information from image frames for navigation purpose they have to be classified. Classification...
This paper presents a novel traffic sign recognition system comprising of: (i) Color/shape classification, (ii) Pictogram extraction, (iii) Features selection and, (iv) Lyapunov Theory-based Radial Basis Function neural network (RBFNN). In the proposed system, traffic signs are first segmented and classified with regard to its unique color and shape in order to partition a large set of data into smaller...
Remote sensing classification is the core of converting satellite image to useful geographic information. Many methods have been proposed for improving classification accuracy, however, the results are always dissatisfied. The reason is that there is serious spectral overlay phenomenon between classes which decrease the classification accuracy. This paper introduced an evidential reasoning "soft"...
ADS40 images with High spatial resolution have more spatial characteristics as well as spectral characteristics than low-resolution data. In this paper,an object-oriented classification method based on multi-scale segmentation is introduced to classify ADS40 image of Taiyuan city. Firstly,a multi-scale segmentation algorithm is applied to get objects.Then,the features of objects,such as spectral,...
This paper presents a novel algorithm based on the gradient direction to separate the multiple attaching and overlapping objects. The idea is based on the fact that the gradient directions of north,east,south,and west neighbourhood pixels are divergent when the gradient direction of the pixel located in the boundary region is used as a reference line.The proposed algorithm is composed of three steps:image...
A grading system was developed to classify chestnut automatically into various grades of quality in terms of size. The chestnut is scanned with a color charge-coupled-device camera and then the size is extracted by image processing. In the image processing there are two kinds of algorithm, one is the minimum enclosing rectangle (MER), and the other is the distance between centroid and border (DCB)...
The full polarimetric information of the target from polarized Synthetic Aperture Radar (POLSAR) enables us to implement recognition and classification of remote sensing images more effectively. Based on the analysis of typical polarized target decomposition and classification, the issue proposes a new scheme for iterative classification of polarimetric SAR image, which blends the outcomes of Yamaguchi...
We proposed fuzzy inference schemes to address the changes of the lighting environment problems: the illumination of the images captured from camera installed on a moving vehicle also varies from frame to frame. First, the input image is checked with a fuzzy inference method to evaluate the illumination conditions in order to apply appropriate preprocessing operations to get a better result. To overcome...
Composite Strain Encoding (C-SENC) is a new MRI technique that acquires cardiac functional and viability images simultaneously. It combines the use of Delayed Enhancement (DE) imaging to identify the infracted (dead) tissue inside the heart muscle and the ability to image myocardial deformation from the Strain Encoding (SENC) imaging technique. In this work, a new multi-stage technique is proposed...
The objective of this paper is to evaluate the classification performance of several feature extraction and classification methods for exotic wood texture images as dataset. The Gray Level Co-occurrence Matrix, Local Binary Patterns, Wavelet, Ranklet, Granulometry, and Laws' Masks will be used to extract features from the images. The extracted features are then fed into five classification techniques:...
Detection of outliers and relevant features are the most important process before classification. In this paper, a novel semi-supervised k-means clustering is proposed for outlier detection in mammogram classification. Initially the shape features are extracted from the digital mammograms, and k-means clustering is applied to cluster the features, the number of clusters is equal with the number of...
This paper deals with the technique to detect automatically the changes of land use pattern over a particular period of time with visual effect. Two land use maps (obtain from satellite picture) of the same location with some period interval have been taken as inputs. This tool calculates the RGB values, latitude and longitude of each pixel of the map. The pixel based changes of the land use classes...
The principle of Support Vector Machine based on spot is to choose an appropriate scale to split the image into a series of segmentation, according to certain strategy using spectral information. And this principle ensures the spectral features of the majority of patch pixel similar. This method gathers statistics of each pixel value in the spot and obtains the mean value of each band to replace the...
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