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Crowd density estimation is an effective automated video surveillance technique to ensure crowd safety. In spite of various efforts being taken to estimate crowd density, it remains a challenging task. This paper proposes a new texture feature-based approach for the estimation of crowd density where two efficient texture features namely Local Binary Pattern (LBP) and Gabor Filter are used. The LBP...
Prostate Cancer is one of the most common types of cancer found in men aged over 40 years. Detection and staging is the most critical step for pathologists. This research supports the development of Computer Aided Detection system capable of grading prostate cancer with high accuracy and less human involvement. Real patient dataset collection is a challenge, we collected real and graded dataset from...
Extract facial feature is considered as the most important step in face recognition systems. Several researches have been made to improve facial feature extraction techniques. This paper proposes hybrid global and local feature based on Gabor filter bank and double coding local binary pattern (LBP). The proposed features are concatenated and reduced using generalized discriminant analysis (GDA). The...
Non-Local means (NL-Means) algorithm is an effective denoising algorithm, but very dependent on the measured non-local similarity image blocks. In order to obtain as many similar image blocks as possible, we propose the Discrete Fourier Transform of local Gabor feature (LGF-DFT) which is rotation invariant and noise robust to measure the image blocks similarity, and fully utilize structural information...
Aiming at the realization of national feature extraction, an improved face recognition method is proposed in order to preserve some essential local features. Gabor featurebased on bi-directional two-dimensional principal component analysis ((2D)2PCA) is applied for face images. Firstly, Gabor features of different orientations and scales are extracted by the convolution of Gabor filter bank. Secondly,...
Change detection techniques for remote sensing images are increasingly applied to many fields, such as disaster monitoring, vegetation coverage analysis and so on. How to improve the accuracy of detection has been a critical topic that confuse the researchers for a long time. In this paper, a method combining multiscale segmentation and fusion for high-resolution images is presented. The strategy...
Nowadays content-based image retrieval (CBIR) is the most powerful and popular method for retrieving color, shape, and texture. In this paper, we proposed content based image retrieval using enhanced Gabor wavelet transform for increasing the retrieval efficiency. Gabor wavelet transform (GWT) is widely concentrated on the combination of features of plane wave and Gabor function to form non-orthogonal...
Convolutional Neural Networks (CNN) are being increasingly used in computer vision for a wide range of classification and recognition problems. However, training these large networks demands high computational time and energy requirements; hence, their energy-efficient implementation is of great interest. In this work, we reduce the training complexity of CNNs by replacing certain weight kernels of...
In view of the traditional saliency detection method gets imprecise and vague region boundary, so that the detected object is not connected, the paper proposes image visual saliency feature extraction based on multi-scale tensor space. The method introduces the tensor space, using multiple low-level image features to construct the tensor space, after reducing dimension the image space structure and...
In this paper, an automatic recognition method of Chinese characters in static complex background is proposed and studied. Firstly, an feature extraction model combing Gabor filter and Sobel operator to is designed to get Chinese characters area. Secondly, K-means clustering algorithm is used to distinguish between the character area and the background area. Then, according to structure characteristics...
In uncontrolled environments, the major challenges in face recognition, such as illumination variation, occlusion, facial expressions and poses, greatly affect the performance of Facial Recognition Systems (FRS) especially those based on 2D information. We introduce, in this paper, a novel feature extraction approach named GLBSIF for face recognition in an uncontrolled environment. In our method,...
Verification of individual identity through the process of biometric identification involves comparison between an encoded value and a stored value of the biometric feature in question. The effectiveness of a multimodal user authentication system is greater, but so is its complexity. The system error rate is reduced by the fact that multiple biometric features are combined, thus solving the weakness...
The paper presents an algorithm allowing for automatic detection of squat flaws in railway rails. These flaws can pose a threat to the safety of railway traffic. A Gabor filter bank along with SVM classifier were used in the detection process. The optimal number of features used to discriminate between squat and the area without squat as well as the parameters for classifier were selected with the...
In this paper, we conduct a comprehensive study to identify the most discriminative features that address the interpersonal variability to perform efficient human emotion recognition task. We consider three commonly used feature extraction techniques, namely, the Local Binary Patterns (LBP), the Scale-Invariant Feature Transform (SIFT) and the curvelet transforms to extract features from the images...
Scoring facial wrinkles is a crucial process to specify exact treatment for wrinkles or to understand the effectiveness of the applied treatment to wrinkles. In this study, only forehead wrinkles are examined instead of the whole facial wrinkles. Detection and quantification of the forehead wrinkles are tried to be performed automatically by computers. For this purpose, the features are extracted...
Comparing with the steganalysis methods based on the feature sets assembled as histograms of filtered images, their improved versions incorporating the change probabilities of coefficients in the embedding domain provide more excellent performance for content-adaptive JPEG steganography, the weight allocation of feature statistical samples is the most important. In this paper, we propose a new weight...
Facial Expression Recognition performs a primary role Human computer interaction (HCI) field. The author proposed hybrid approach which performed better in recognizing facial expression. In the paper, the emotions are detected by calculating the feature vector of the input facial image using Hybrid approach and distinguish or classify the features using SVM classifier. The performance of recognition...
Classifying ancient Arabic manuscripts based on handwriting styles is one of the important roles in the field of paleography. Recognizing the style of handwriting in Arabic manuscripts helps in identifying the origin and date of ancient documents. In this paper we proposed using segmented letters from Arabic manuscripts to recognize handwriting style. Both Gabor Filters (GF) and Local Binary Pattern...
We present a novel method for robotic mower's lawn obstacle avoidance as well as motion control, which is based on the Gabor texture classification and drivable region search methods. In our approach, a camera is applied to obtain real-time image streams of lawn scenes, Gabor filters are then applied for extracting robust texture features. Based on the compressed features, a SVM model is trained and...
Hyperspectral face recognition provides improved classification rates due to its abundant information in the face cubes of every subject in hyperspectral face databases. However, it is less popular in face recognition due to its difficulty in data acquisition, low signal-to-noise ratio, and high dimensionality. The authors compare five existing descriptors that are frequently used in 2D face recognition,...
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