local binary patterns (LBPs) are used for effective texture representation in various applications. This study explores the clustering consistency and stability of image segmentation when distance-based clustering met...
详细信息
local binary patterns (LBPs) are used for effective texture representation in various applications. This study explores the clustering consistency and stability of image segmentation when distance-based clustering methods are used with an LBP. Because data are described by features and attributes, distances among data are also dominated by the definition of features. Moreover, four popular LBP encoding schemes for segmenting computed tomography (CT) images by using fuzzy C-means are discussed and compared. The experimental results demonstrate several notable phenomena: When the pixels are encoded in different LBP encoding schemes, the distance between these pixels varies considerably. The experimental results indicate that each LBP encoding scheme emphasizes a specific image texture that dominates how pixels are described in the feature space and thus affects the clustering results. Based on the evaluation of CT image segmentation by using the clustering inconsistency index, linear and corner-like LBPs are particularly suitable for clustering longitudinal sections and cross sections of CT images, respectively.
For intelligent traffic monitoring systems and related applications, detecting vehicles on roads is a vital step. However, robust and efficient vehicles detection is still a challenging problem due to variations in th...
详细信息
For intelligent traffic monitoring systems and related applications, detecting vehicles on roads is a vital step. However, robust and efficient vehicles detection is still a challenging problem due to variations in the appearance of the vehicles and complicated background of the roads. In this paper, we propose a simple and effective vehicle detection method based on local vehicle's texture and appearance histograms feed into clustering forests. The interdependency of vehicle's parts locations is incorporating within a clustering forests framework. local binary pattern-like descriptors are utilized for texture feature extraction. Through utilizing the LBP descriptors, the local structures of vehicles, such as edge, contour and flat region can be effectively depicted. The align set of histograms generated concurrence with LBPs spatial for random sampled local regions are used to measure the dissimilarity between regions of all training images. Evaluating the fit between histograms is built in clustering forests. That is, clustering discriminative codebooks of latent features are used to search between different LBP features of the random regions utilizing the Chi-square dissimilarity measure. Besides, saliency maps built by the learnt latent features are adopted to determine the vehicles locations in test image. Effectiveness of the proposed method is evaluated on different car datasets stressing various imaging conditions and the obtained results show that the method achieves significant improvements compared to published methods.
Sometimes realistic face representation is confronted with blur or low-resolution face images, as a result, existing classification methods are not powerful and robust enough. This paper proposes a novel face represen...
详细信息
Sometimes realistic face representation is confronted with blur or low-resolution face images, as a result, existing classification methods are not powerful and robust enough. This paper proposes a novel face representation approach (GLL) which fuses Gabor filter, local binary pattern (LBP) and local Phase Quantization (LPQ). In the process of Gabor filter, it uses Gabor wavelet functions with two scales and eight orientations to capture the salient visual properties in face image. On this basis of Gabor features, we acquire LBP features and LPQ features, respectively, so as to fully explore the blur invariant property and the information in the spatial domain and among different scales and orientations. Experiments on both CMU-PIE and Yale B demonstrate the effectiveness of our GLL when dealing with different condition face data sets. (C) 2012 Elsevier B.V. All rights reserved.
In this letter, a fast digital image stabilization method based on local binary pattern (LBP) for real time applications is presented. The LBP approach utilized in this work enables efficient representation of the ima...
详细信息
In this letter, a fast digital image stabilization method based on local binary pattern (LBP) for real time applications is presented. The LBP approach utilized in this work enables efficient representation of the image frames in 1-bit depth resolution. A simple Boolean exclusive-OR (XOR) based matching criterion is employed to decide global motion vector between consecutive image frames. The constant velocity model based Kalman filtering is executed on the global motion vectors to obtain smoothed frame positions. Experiments show that the proposed approach provides comparable or better performance against the methods at the same category by requiring lower computational complexity.
In this paper we focus on appearance features particularly the local binary patterns describing the manual component of Sign Language. We compare the performance of these features with geometric moments describing the...
详细信息
In this paper we focus on appearance features describing the manual component of Sign Language particularly the local binary patterns. We compare the performance of these features with geometric moments describing the...
详细信息
In today's digital era, secret data hiding has become important part of information security. local binary pattern (LBP) operator which exploits the local intensity relationship of a coordinate with its neighborho...
详细信息
ISBN:
(纸本)9781509020287
In today's digital era, secret data hiding has become important part of information security. local binary pattern (LBP) operator which exploits the local intensity relationship of a coordinate with its neighborhood has been successfully implemented in texture classification and image retrieval. This paper proposes a novel steganographic technique based on LBP operator in wavelet domain for embedding and extraction of secret information. Proposed technique has been implemented in Matlab. Image quality metrics PSNR and SSIM are used to compare proposed technique with LSB substitution method.
local binary pattern (LBP) and Texton are both widely used texture analysis techniques. In this paper we propose a patch-based texture classification method that takes advantage of both LBP and Texton. Unlike the trad...
详细信息
ISBN:
(纸本)9781457713033
local binary pattern (LBP) and Texton are both widely used texture analysis techniques. In this paper we propose a patch-based texture classification method that takes advantage of both LBP and Texton. Unlike the traditional LBP methods that describe a texture with the occurrence of local binary patterns in the entire image, we compute the LBP histogram in a small region around each pixel to capture the local structure information. The texton learning method is then performed on these LBP histograms, resulting in a texture classification algorithm that outperforms the traditional LBP-based methods due to its preservation of local structure information. It also outperforms the traditional filtering-based texton methods due to its robustness to orientation and illumination. Experimental results on two benchmark databases validate the advantages of the proposed method.
Measurement of visual quality is of fundamental importance for numerous image and video processing applications. This paper presented a novel and concise reduced reference (RR) image quality assessment method. Statist...
详细信息
ISBN:
(纸本)9780819494337
Measurement of visual quality is of fundamental importance for numerous image and video processing applications. This paper presented a novel and concise reduced reference (RR) image quality assessment method. Statistics of local binary pattern (LBP) is introduced as a similarity measure to form a novel RR image quality assessment (IQA) method for the first time. With this method, first, the test image is decomposed with a multi-scale transform. Second, LBP encoding maps are extracted for each of subband images. Third, the histograms are extracted from the LBP encoding map to form the RR features. In this way, image structure primitive information for RR features extraction can be reduced greatly. Hence, new RR IQA method is formed with only at most 56 RR features. The experimental results on two large scale IQA databases show that the statistic of LBPs is fairly robust and reliable to RR IQA task. The proposed methods show strong correlations with subjective quality evaluations.
This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images...
详细信息
ISBN:
(纸本)9781424419982
This paper presents a fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images. The underlying idea is to benefit from both the robust image representation capability of local binary patterns, and the compact representation capability of local appearance-based face recognition. In the proposed method, prior to local appearance modeling, the input face image is transformed into the local binary pattern domain. The obtained LBP-representation is then decomposed into non-overlapping blocks and on each local block the discrete cosine transform is applied to extract the local features. The extracted local features are then concatenated to construct the overall feature vector. The proposed algorithm is tested extensively on the face images from the CMU PIE and the FRGC version 2 face databases. The experimental results show that the combined approach improves the performance significantly.
暂无评论