In this paper, we proposed a new approach for image clustering to address the adverse effects of noise presented in the images. In particular, the concept of information gain has been incorporated into classical fuzzy...
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In this paper, we proposed a new approach for image clustering to address the adverse effects of noise presented in the images. In particular, the concept of information gain has been incorporated into classical fuzzy c-means (FCM) algorithm in order to develop a robust clustering method. FCM is associated with high sensitivity to noise and produces non-homogenous clustering. To induce robustness to noise, the new clustering technique updates fuzzy membership values and cluster centroids based on information gain. The proposed method produces more homogeneous clustering and its performance can be verified at noisy and noise free images. Experiments have been performed on synthetic, CT liver images and compared with those of classical FCM and one of its robust variants. Moreover, the proposed algorithm has been validated on a data set of 30 carotid artery ultrasound images. Visual inspection of segmented images and clustering quality measures confirm that the proposed approach outperforms other clustering algorithms in comparison. Quantitative measures, in terms of PC and CE, also lead to similar conclusion. Hence, the proposed algorithm is robust to noise and produces homogenous clustering.
In order to reduce the power consumption of OLED displays and guarantee image quality at the same time, a new OLED low-power approach based on hue, saturation and value (HSV) color space is proposed. The approach appl...
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In order to reduce the power consumption of OLED displays and guarantee image quality at the same time, a new OLED low-power approach based on hue, saturation and value (HSV) color space is proposed. The approach applies value and saturation scaling (SS) integration technique to save display power. Further, the original input image is divide into two area, i. e., region of interest (ROI) and region of non-interest, and then a technique, gradually decreasing the value and increasing the saturation from ROI to the edge, is applied to improve image quality which can be evaluated by the mean structural similarity index (MSSIM). The MSSIM quality metric is widely used to evaluate the amount of image distortion and adopted to account for the human visual perception among the image processing community, which divides the original image and the output image into several windows and compares the luminance, the contrast and the structural similarity iwth the other windows. As a result, obvious of power OLED displays is saved without significantly affecting the perceived image quality. The experimental results show that the proposed approach keeps the MSSIM at a high level of 80.31% and save 57.93% OLED power when the gradual level equals 15.
Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectu...
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Domes are architectural structural elements typical for ecclesiastical and secular grand buildings, like churches, mosques, palaces, capitols and city halls. The current paper targets the problem of segmentation of do...
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Image re-ranking aims at improving the precision of keyword-based image retrieval, mainly by introducing visual features to re-rank. Many existing approaches require offline training for every keyword, which are unsui...
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In this paper, a new unsupervised learning algorithm, namely Nonnegative Discriminative Feature Selection (NDFS), is proposed. To exploit the discriminative information in unsupervised scenarios, we perform spectral c...
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This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with...
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Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectu...
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Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate.
This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with...
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ISBN:
(纸本)9781467301732
This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the sub-template size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.
Churn prediction model guides the customer relationship management to retain the customers who are expected to quit. In recent times, a number of tree based ensemble classifiers are used to model the churn prediction ...
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ISBN:
(纸本)9781467317139
Churn prediction model guides the customer relationship management to retain the customers who are expected to quit. In recent times, a number of tree based ensemble classifiers are used to model the churn prediction in telecom. These models predict the churners quite satisfactorily;however, there is a considerable margin of improvement. In telecom, the enormous size, imbalanced nature, and high dimensionality of the training dataset mainly cause the classification algorithms to suffer in accurately predicting the churners, in this paper, we use Genetic Programming (GP) based approach for modeling the challenging problem of churn prediction in telecom. Adaboost style boosting is used to evolve a number of programs per class. Finally, the predictions are made with the resulting programs using the higher output, from a weighted sum of the outputs of programs per class. The prediction accuracy is evaluated using 10 fold cross validation on standard telecom datasets and a 0.89 score of area under the curve is observed. We hope that such an efficient churn prediction approach might be significantly beneficial for the competitive telecom industry.
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