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The ads exposure frequency in a TV is very important for the pricing of the advertising. If we count this exposure frequency by person, it will be very time consuming and error-prone. In this paper, we propose an approach and design a system for searching and counting the number of banner ads appearing in sports videos. The searching proceeds by matching feature points from pre-specified sample ads...
In this paper we propose a fast and robust descriptor for multiple view object recognition using a small number of training examples. In order to design a descriptor to be discriminative between many different object appearances, we base it on a combination of invariant color, edge and texture descriptors. We use a color descriptor based on a HSV histogram - as it is robust to size and position of...
Object re-identification and tracking in non-overlapping cameras is a challenging problem due to the variation of the object's appearance, linked to the different view angle, distance and color variation in different cameras. We present a computationally efficient real time human tracking algorithm, which can track objects inside the field of view (FOV) of a camera, re-identify objects that exit and...
Practical tracking system must be able to adjust the tracking windows adaptively according to the size-changes of the tracked objects; otherwise it can not track the objects with obvious size-changes accurately. Based on the visual theory, and combined with the primal sketch of the objects extracted by the Otsu method as well as the changes of the elements-number as the measure information, this paper...
Color and shape descriptions of an image are the most widely used visual features in content-based image retrieval systems. Feature vectors for shape and color can be combined to improve the performance of the content-based image retrieval systems. In this paper, a novel image retrieval method integrating HSV color quantization and curve let transform is proposed. By analyzing properties of HSV(Hue,...
A new video surveillance object recognition algorithm is presented, in which improved invariant moments and length-width ratio of object are extracted as shape feature, while color histograms of object are utilized as color feature. On the combination of shape and color features, object recognition is achieved. Based on the algorithm, an intelligent video surveillance system is implemented. Test results...
We study traffic sign detection on a challenging large-scale real-world dataset of panoramic images. The core processing is based on the Histogram of Oriented Gradients (HOG) algorithm which is extended by incorporating color information in the feature vector. The choice of the color space has a large influence on the performance, where we have found that the CIELab and YCbCr color spaces give the...
In this work we address the problem of forest species recognition which is a very challenging task and has several potential applications in the wood industry. The first contribution of this work is a database composed of 22 different species of the Brazilian flora that has been carefully labeled by expert in wood anatomy. In addition, in this work we demonstrate through a series of comprehensive...
In this paper we propose a coin recognition system using a statistical approach and apply it to the recognition of Jordanian coins. The proposed method depends on two features in the recognition process: the color of the coin, and its area. The recognition process consists of several steps. Firstly, a gray-level image is extracted from the original colored image. The image is then segmented into two...
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This...
Image category recognition is important to access visual information on the level of objects and scene types. This paper presents an automatic recognition system of scene and object with PCA-SICEF feature for digital color images. SICEF (scale-invariant color and edge feature) is an extension of the conventional local SIFT (scale-invariant feature transform) feature, which only include edge invariance...
Against vertical Sobel operator that most license plate detection (LPD) algorithms adopt, this paper presents a robust and real-time preprocessing method to enhance both edge density and intensity of license plates under various outdoor and indoor environments. The proposed method applies HL subband feature of 2D discrete wavelet transform (DWT) twice to significantly highlight the vertical edges...
This paper presents a new descriptor for object categorization and pedestrian identification applications. One of the main drawbacks of shape-context descriptor is its vulnerability and distinctness to color images. We propose a spherical descriptor that simultaneously adopts the spatial and color information as a discriminative representation. Based on the descriptor, this paper also contributes...
In the context of object recognition, it is useful to extract, from the images, efficient indexes that are insensitive to the illumination conditions, to the camera scale factor and to the 2D position and orientation of the object. In this paper, we propose to cope with this invariance problem by normalizing the images according to these parameters in a preprocessing step. This spatio-colorimetric...
We present a framework intended to assist users in the task of tagging pictures with content descriptors. Histogram- or correlogram features of manually indicated regions of interest are extracted from a few training images; probabilistic diffusion over these prototypes is used to analyze further images. Since speed is pivotal in interactive applications, we apply a fast algorithm for computing local...
Each moving object contains particular unique signatures that can be used for pattern classification via object recognition and identification. Information extracted from the spatial object feature recognition can be provided by independent basis functions to represent actual physical attributes of the moving objects. Compared with principal component analysis, independent component analysis is a...
This paper presents a recognition method for natural images based on color texture histograms in the context of image interpretation and scene modeling. A color histogram of sums and differences is proposed to obtain texture features which are faster to compute than correlograms ( i.e., colored version of co-occurrence matrices) and improving substantially object recognition. Outdoor natural images...
This paper proposes a new technique for paper currency recognition. In this technique, three characteristics of paper currencies including size, color and texture are used in the recognition. By using image histogram, plenitude of different colors in a paper currency is computed and compared with the one in the reference paper currency. The Markov chain concept has been employed to model texture of...
The colorful reef fishes are always most conspicuous and attractive by their vibrant colors in an aquarium. Usually, aquarium provides the visitors with pictures and some description of the reef fishes in the exhibition tank. However, an aquarium equipping with an automatic reef fish recognition system can add attractions and help aquarium to educate people about these fishes. For assistance in distinguishing...
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