Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a perso...
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ISBN:
(纸本)9781479956869
Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a person to manually type in the marks into a spreadsheet. This method is found to be time consuming, not cost effective and prone to human mistakes. Thus, a number recognition system is developed using local binary pattern (LBP) technique to extract and convert students' identity numbers and handwritten marks on assessment forms into a spreadsheet. The training data contain three sets of LBP values for each digit. The recognition rate of handwritten digits using LBP is about 50% because LBP could not fully describe the structure of the digits. Instead, LBP is useful in term of scaling the digits '0 to 9' from the highest to the lowest similarity score as compared with the sample using chi square distance. The recognition rate can be greatly improved to about 95% by verifying the ranking of chi square distance with the salient structural features of digits.
In this paper, we present a decision level fused local Morphological pattern Spectrum(PS) and local binary pattern (LBP) approach for an efficient shape representation and classification. This method makes use of Eart...
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ISBN:
(纸本)9780769551005
In this paper, we present a decision level fused local Morphological pattern Spectrum(PS) and local binary pattern (LBP) approach for an efficient shape representation and classification. This method makes use of Earth Movers Distance(EMD) as the measure in feature matching and shape retrieval process. The proposed approach has three major phases : Feature Extraction, Construction of hybrid spectrum knowledge base and Classification. In the first phase, feature extraction of the shape is done using pattern spectrum and local binary pattern method. In the second phase, the histograms of both pattern spectrum and local binary pattern are fused and stored in the knowledge base. In the third phase, the comparison and matching of the features, which are represented in the form of histograms, is done using Earth Movers Distance(EMD) as metric. The top-n shapes are retrieved for each query shape. The accuracy is tested by means of standard Bulls eye score method. The experiments are conducted on publicly available shape datasets like Kimia-99, Kimia-216 and MPEG-7. The comparative study is also provided with the well known approaches to exhibit the retrieval accuracy of the proposed approach.
LBP is a successful hand-crafted feature descriptor in computer vision. However, in the deep learning era, deep neural networks, especially convolutional neural networks (CNNs) can automatically learn powerful task-aw...
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Diabetic Retinopathy (DR) is a condition caused by diabetes that affects the blood vessels in the retina. Detecting the disease early and providing appropriate treatment are crucial in slowing its progression. Therefo...
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In this paper, we propose a combined classifier model based on Height functions (HF) and local binary pattern (LBP) to classify shapes accurately. The height functions are insensitive to geometric transformations and ...
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ISBN:
(纸本)9781479930807
In this paper, we propose a combined classifier model based on Height functions (HF) and local binary pattern (LBP) to classify shapes accurately. The height functions are insensitive to geometric transformations and nonlinear deformations and LBP is capable of capturing the region information. We propose to integrate these two techniques for accurate shape classification. The Dynamic Programming (DP) in case of HF and the Earth Movers Distance (EMD) metric in case of LBP were respectively employed to obtain similarity values and hence fused to classify given query shape based on minimum similarity value. The experiments are conducted on publicly available shape datasets namely MPEG-7, Kimia-99, Kimia-216, Myth and Tools-2D and the results are presented by means of Bull's eye score and precision-recall metric. The comparative study is also provided with the well known approaches to exhibit the retrieval accuracy of the proposed approach. The proposed approach shows better results compared to other algorithms.
Facial makeup is one of the problems that are caused decrease in the performance of face recognition algorithms. In this paper, a novel method is proposed to handle facial makeup in face recognition. The combining of ...
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ISBN:
(纸本)9781479953592
Facial makeup is one of the problems that are caused decrease in the performance of face recognition algorithms. In this paper, a novel method is proposed to handle facial makeup in face recognition. The combining of local binary pattern (LBP) and Dual-Tree Complex Wavelet Transform (DT-CWT) is applied to face image for feature extraction. Then, by combining entire of LBP and DT-CWT feature vectors, the final feature vectors are generated and classified by the Support Vector Machine (SVM). Promising results were achieved for makeup-invariant face recognition on the available image database based on the present method compared to several state-of-the-art methods.
local binary pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and...
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ISBN:
(纸本)9781479953530
local binary pattern (LBP) is a simple yet powerful method for image feature extraction in pattern recognition and image processing. However, the LBP operator of each pixel mainly depends on its neighboring pixels and emphasizes on local information too much. From the practical viewpoint, the information is quite limited if we consider the LBP operator in isolation, especially for a large image. To deal with this issue, we propose ultra LBP (U-LBP), which consider the relationship among different LBP operators. The proposed method cannot only get the local but also ultra local information. The effectiveness of the proposed algorithm is investigated on gender recognition and digit recognition, respectively. The experimental results show that the proposed method outperforms the traditional LBP.
Classification of environmental sounds is a fundamental procedure for a wide range of real-world applications. In this paper, we propose a novel acoustic feature extraction method for classifying the environmental sou...
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ISBN:
(纸本)9781479928934
Classification of environmental sounds is a fundamental procedure for a wide range of real-world applications. In this paper, we propose a novel acoustic feature extraction method for classifying the environmental sounds. The proposed method is motivated from the image processing technique, local binary pattern (LBP), and works on a spectrogram which forms two-dimensional (time-frequency) data like an image. Since the spectrogram contains noisy pixel values, for improving classification performance, it is crucial to extract the features which are robust to the fluctuations in pixel values. We effectively incorporate the local statistics, mean and standard deviation on local pixels, to establish robust LBP. In addition, we provide the technique of L-2-Hellinger normalization which is efficiently applied to the proposed features so as to further enhance the discriminative power while increasing the robustness. In the experiments on environmental sound classification using RWCP dataset that contains 105 sound categories, the proposed method produces the superior performance (98.62%) compared to the other methods, exhibiting significant improvements over the standard LBP method as well as robustness to noise and low computation time.
Robust face recognition from blurred images is an important and challenging problem. We propose sample-wise kernel estimation (SWKE). For each sharp gallery sample, an optimal blur kernel making the distance between p...
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In this paper, a novel method for human age estimation is proposed. This research is novel in the following four ways. First, the in-plane rotation of face region is compensated based on the detected positions of two ...
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