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A novel local texture feature extraction algorithm is proposed based on histogram of oriented gradient domain texture tendency (HOGTT). Classical HOG descriptor proves to be sensitive to rotation transformation, though it is insensitive to illumination and scale changes. The intrinsic texture tendency of tyre tread image has obvious consistency and is robust to different types of images transformation...
To study the problem of real-time and accuracy of the image retrieval algorithm of embedded system with scale, rotation and illumination. Improved SURF algorithm, which is applied to the binary image feature extraction, improve the real-time performance of the image, the use of LSH algorithm to establish the index of the image feature database, to avoid duplicate feature extraction, the use of LSH...
In this paper, a variation in the Local Binary Pattern (LBP) called Modified Dominant Directional LBP (MDDLBP) is proposed. In this method, the direction of the feature with respect to its central pixel in the LBP is preserved by comparing the neighborhood of the pixel in the four dominant directions such as horizontal, vertical, diagonal and anti diagonal. This method captures complete structure...
Given a query image, retrieving images depicting the same object in a large scale database is becoming an urgent and challenging task. Recently, Compact Description for Visual Search (CDVS) is drafted by the ISO/IEC Moving Pictures Experts Group (MPEG) to support image retrieval applications, and it has been published as an international standard. Unfortunately, with regard to applications with hugely...
In the field of Digital Image Processing Content Based Image Retrieval is becoming very popular. Google and Yahoo have tools on Digital Image Processing. They are known to be Google Images and Yahoo! Images Search. They are based on textual annotation of images. In textual annotations with the help of keywords images are retrieved. This is not very much effective approach as their performances are...
Face recognition is an important area in biometrics and computer vision. A lot of feature extraction can handle face recognition method such as checking pixel neighbor. Local Binary Pattern, Local Graph Structure, and Symmetric Local Graph Structure are an operator of the feature extraction. This research called Extended Symmetric Local Graph Structure which it is an improvement operator from SLGS...
With the advent of the ‘big data’ era, a huge number of images are produced every day. Traditional image compression methods no longer satisfy the demand to store and transmit them. In this paper, we face this challenge and take advantage of the correlations existing between images to achieve a higher compression rate. We propose an image compression system that encodes each image by referencing its...
Invention of the digital camera and also cell phones with powerful cameras with moderate and low pricing system has given the common man the privilege to capture his world in pictures anywhere, at any time, and conveniently share them with others. This has resulted the generation of volumes of images. These factors have created numerous possibilities and finally created interest among the researchers...
Deep convolutional neural networks (CNN) have recently been shown in many computer vision and pattern recognition applications to outperform by a significant margin state-of-the-art solutions that use traditional hand-crafted features. However, this impressive performance is yet to be fully exploited in robotics. In this paper, we focus one specific problem that can benefit from the recent development...
Researchers exploring problems in image matching tasks face the curse of perceptual aliasing that is originally used in characterizing a sensing process. Perceptual aliasing occurs when the one-to-one mapping relations between world states (objects) and their representations (descriptors) are not maintained. In this paper, we introduce a novel method for quantifying perceptual aliasing. Our method...
One of the constant challenges in image analysis is to improve the process for obtaining distinctive object characteristics. Feature descriptors usually demand high dimensionality to adequately represent the objects of interest. The higher the dimensionality, the greater the consumption of resources such as memory space and computational time. Scale-Invariant Feature Transform (SIFT) and Speeded Up...
The spatial geometrical features of the objects are widely used in the image matching and retrieval. The popular algorithms of the spatial feature detection are designed for gray images, which failed to make use of the color information in color images. However, the color information is absolutely nontrivial in discrimination of different objects, vacancy of which would lead to miss judgment. Based...
Interest point detection is an important research area in the field of image processing and computer vision. In particular, image retrieval and object categorization heavily rely on interest point detection from which local image descriptors are computed for image matching. In general, interest points are based on luminance, and color has been largely ignored. However, the use of color increases the...
Different image has different characteristic attributes. And the similarity between images is the measure distance of these characteristic attributes. Three kinds of similarity metric models, which are the models based on histogram statistic, based on pixels and based on the differences between pixels, were described. Then the performances of these three kind models have been analyzed from various...
In this paper, we draw Local Binary Pattern (LBP) and main color descriptor into content-based video indexing and retrieval. LBP is a powerful texture descriptor for its tolerance against illumination changes and its computational simplicity. Main color descriptor is used for representing main color distribution of the image. We propose a simplified LBP (S-LBP) operator as the texture descriptor....
We describe a robust feature descriptor called soft ordinal spatial intensity distribution (soft OSID) that is invariant to any monotonically increasing brightness changes. In traditional histogram-based feature descriptors, each pixel is explicitly assigned to a single histogram bin, making them not robust to image deformations and appearance changes. In this paper, we present a feature descriptor...
Color image retrieval based on histogram is analyzed and a novel method is proposed based on the image edge information. Firstly, the image edge is extracted by the use of the color vector angles because of its character which is insensitive to illumination but sensitive to hue and saturation. Then, the color vector angle histogram of the image edge is constructed to describe the image feature. With...
In this work a new method to retrieve images with similar lighting conditions is presented. It is based on automatic clustering and automatic indexing. Our proposal belongs to Content Based Image Retrieval (CBIR) category. The goal is to retrieve from a database, images (by their content) with similar lighting conditions. When we look at images taken from outdoor scenes, much of the information perceived...
This paper provides an effective content-based web image searching engine based on SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. To decrease unavailable features matching, a dynamic probability function...
This paper presents an algorithm based on SIFT features. It calculates key points in the image and extracts the feature of the image by calculating the key points' orientation and modulus of the gradient. The similarity between two images is computed using Euclidean distance. The experiment shows that the feature is invariant to image scaling translation, rotation, and partly invariant to illumination...
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