Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an i...
详细信息
ISBN:
(纸本)9781614995128;9781614995111
Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the local binary pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.
Face perception is one of the most important tasks in robot vision especially for service robots. The spatially enhanced local binary pattern histogram (eLBPH) method has been proved to be effective for facial image r...
详细信息
ISBN:
(纸本)9781467396752
Face perception is one of the most important tasks in robot vision especially for service robots. The spatially enhanced local binary pattern histogram (eLBPH) method has been proved to be effective for facial image representation and analysis, but the expression factor isn't considered and the region-dividing method is rough. In this paper, inspired by the biological mechanism of human memory and face perception, we improve the eLBPH and propose a new method, expression-specific weighted local binary pattern histogram (EWLBPH). Accordingly, the new method introduces a semantic division process and an extended modulation process into the classical eLBPH. What's more, for the facial expression recognition, we propose a novel method which utilizes the convolutional deep belief network (CDBN) to extract discriminative information and represent them effectively. Finally, through experiments we verify the rationality and effectiveness of the improvement and two psychophysical findings.
Automated age estimation from facial images has recently drawn a lot of attention from the research community emerging as a key technology with numerous applications ranging from access control to human machine intera...
详细信息
ISBN:
(纸本)9781467366731
Automated age estimation from facial images has recently drawn a lot of attention from the research community emerging as a key technology with numerous applications ranging from access control to human machine interaction. In this research study, we explore a vision-based approach for the estimation of age groups from face images. The local binary pattern operator is applied to derive a set of hybrid features composed local and global characteristics from the face. A histogram of features is constructed based on the concatenation of locally produced histogram vectors from grid cells of face images. Hierarchical feature selection is described for the classification process where age ranges determined automatically in a tree-based fashion. Feature selection is based on the proximity of instances belonging to the same range is applied to obtain the most discriminative traits at each level of the defined age range. Experimental results carried out on a publicly available dataset confirmed the efficiency for the method to better cluster and estimate different age groups for different face images.
Due to the popularity of multimedia technology and digital world, thousands of videos are accessed through internet in seconds. Most of the videos, available in internet for public access are non-edited videos. Effici...
详细信息
ISBN:
(纸本)9781509002252
Due to the popularity of multimedia technology and digital world, thousands of videos are accessed through internet in seconds. Most of the videos, available in internet for public access are non-edited videos. Efficient way of searching and storage need an efficient method of annotation. Automatic cut detection is the first stage of any automatic annotation process. In this paper we addressed the problem of video segmentation of only non-edited videos by classifying the boundary and non-boundary frames. The efficiency of intensity based cut detection methods decrease with variation of intensity of the scene. The local binary pattern is one of the texture feature which provides a strong spatial correlation among the neighboring pixels, which is also invariant to light variation. Therefore in the proposed method, the block based center symmetric local binary pattern feature vector is used for the detection of shot boundaries in a video. The Euclidean distance between the consecutive frame's feature vector is chosen as the similarity measure which is compared with a threshold value to detect the hard cuts in a non-edited video. The proposed algorithm is experimented with seven test videos and its efficacy is validated with few existing popular approaches.
The paper proposes a script classification method which is based on textural analysis of the script types. In the first stage, each letter is coded by the equivalent script type, which is defined by its baseline posit...
详细信息
ISBN:
(纸本)9783319261812;9783319261805
The paper proposes a script classification method which is based on textural analysis of the script types. In the first stage, each letter is coded by the equivalent script type, which is defined by its baseline position. Obtained coded text is subjected to the adjacent local binary pattern analysis to extract the features. The result shows the diversity of the extracted features between scripts, which makes the feature classification easier. It is the basis for decision-making process of the script identification by automatic classification. The proposed method is tested on an example of synthetic and historical German printed documents written in Antiqua and Fraktur scripts. The experiment shows very positive results, which proved the correctness of the proposed algorithm.
Recognition of spontaneous emotion would significantly influence human-computer interaction and emotion-related studies in many related fields. This paper endeavors to explore a holistic method for detecting emotional...
详细信息
ISBN:
(纸本)9781509002870
Recognition of spontaneous emotion would significantly influence human-computer interaction and emotion-related studies in many related fields. This paper endeavors to explore a holistic method for detecting emotional facial expressions by examining local features. In recent years, examining local features has gained traction for nuanced expression detection. The local binary pattern is one such technique. Using the modified LBP adds a discriminating factor to the examined feature via the addition of an edge detector. Hence, the edge based local binary pattern for the extraction of features in the human face. Using this method, the extracted feature is classified into its valence classes (positive and negative) using an SVM classifier.
This paper presents a high performance hardware architecture of face recognition algorithm based on local binary pattern. Through the software implementation of the algorithm, the optimization of the data's widths...
详细信息
ISBN:
(纸本)9781479984855
This paper presents a high performance hardware architecture of face recognition algorithm based on local binary pattern. Through the software implementation of the algorithm, the optimization of the data's widths and block size can be obtained. Then a hardware structure based on the algorithm is proposed. The histogram statistic and recognition can be handled concurrently with a ping- pang memory and the data throughput can be increased with the pipeline and parallel processing units. The proposed architecture is implemented in the Xilinx Virtext- 7 FPGA VC707 evaluation board and is verified with a large number of training pictures. The design costs 5975 LUTs and the clock frequency can be up to 233MHz. For a library with one hundred thousand faces, the proposed design can recognize 1.7 faces per second and its recognition speed is 74 times faster than the software's in the general CPU platform.
this paper presents a new approach to extract image features for texture classification. The extracted features are obtained by a dominant-completed modeling of the traditional local binary pattern (LBP) operator, whi...
详细信息
ISBN:
(纸本)9781467391047
this paper presents a new approach to extract image features for texture classification. The extracted features are obtained by a dominant-completed modeling of the traditional local binary pattern (LBP) operator, which is robust to image rotation, grey scale changing and insensitive to noise and histogram equalization. The main idea of this texture classification approach is that a dominant center pixel and dominant local difference sign-magnitude transforms (DLDSMT) are used to represent the local region of a texture image. The dominant center pixels represent the gray level of a texture image and they are transformed into a binary code by a global threshold, namely DCLBP_C. The image local differences, by using DLDSMT, are decomposed into two complementary components: the dominant signs and the dominant magnitudes. And they are also transformed into binary codes, namely DCLBP_S and DCLBP_M. By converting DCLBP_S, DCLBP_M, and DCLBP_C features into joint or hybrid distributions, we can obtain our proposed feature. Experimental results reveal that our proposed method outperforms several representative methods.
local binary pattern (LBP) operator is defined as gray-scale invariant texture measure. The LBP operator is a unifying approach to the traditionally divergent statistical and structural models for texture analysis. In...
详细信息
ISBN:
(纸本)9788132222057;9788132222040
local binary pattern (LBP) operator is defined as gray-scale invariant texture measure. The LBP operator is a unifying approach to the traditionally divergent statistical and structural models for texture analysis. In this paper the LBP, its variants along with Gabor filters are used as a texture feature for content-based video retrieval (CBVR). The combinations of different thresholds over different pattern using Gabor filter bank are experimented to compare the retrieved video documents. The typical system architecture is presented which helps to process query, perform indexing, and retrieve videos form the given video datasets. The precision and mean average precision (MAP) are used over the recent large TRECViD 2010 and YouTube Action video datasets to evaluate the system performance. We observe that the proposed variant features used for video indexing and retrieval is comparable and useful, and also giving better retrieval efficiency for the above available standard video datasets.
local binary pattern (LBP) is sensitive to noise. LBP projects local patch to eight-dimension vector by operating subtractions between pixel and its neighborhood. Two adjacent pixel values are generally very close, th...
详细信息
暂无评论