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The technology of specific target detection and recognition in Synthetic Aperture Radar (SAR) image is one of the most important issues especially in the area of remote sensing observation. Aiming at ship detection in complex scenario, this paper presents a universal framework and a novel method called Speed-up Seed point OTSU (SSOTSU) based on OTSU and invoked in the framework. Different from the...
The vision system of an autonomous robot can obtain and analyze the necessary environmental information used for autonomous decisions. The processing and recognition of the images captured through the autonomous robot visual system is discussed in this paper. The discussion mainly includes three key issues, namely the extraction of image region of interest, the canceling of image inverse projection...
Reliable banknote recognition is critical for detecting counterfeit banknotes in ATMs and help visual impaired people. To solve this problem, it was implemented a computer vision system that can recognize multiple banknotes in different perspective views and scales, even when they are within cluttered environments in which the lighting conditions may vary considerably. The system is also able to recognize...
Recognizing complex human actions is very challenging, since training a robust learning model requires a large amount of labeled data, which is difficult to acquire. Considering that each complex action is composed of a sequence of simple actions which can be easily obtained from existing data sets, this paper presents a simple to complex action transfer learning model (SCA-TLM) for complex human...
In order to improve the monitoring capability of officer on watch for the environment around the own ship, cover the shortage of RADAR and AIS in ship behavior recognition field, this paper proposes a ship behavior recognition algorithm based on video analysis. After analyzing the ship behavior we found that the silhouette's size and shape variation of ship in infrared image were related to its behavior...
We propose a system for guiding a visually impaired person toward a target product on a store shelf using visual-auditory feedback. The system uses a hand-held, monopod-mounted CCD camera as its sensor and recognizes a target product in the images using sparse feature vector matching. Processing is divided into two phases: In Phase1, the system acquires an image, recognizes the target product, and...
This article puts forward a kind of huge amounts of multi-object image recognition method -- BVCNN. Firstly, BING method is used to recognize images, which greatly reduces the time of estimating image targets, and makes it possible that quickly identify multiple target images, compared to traditional convolution neural networks only achieving single target image recognition, Secondly, vectorization...
For cross-view action recognition and many real-world visual classification problems, one needs to recognize test data at a particular target domain of interest, while training data are collected at a different source domain. Without eliminating such domain differences, recognition of test data using classifiers trained in the source domain will not be expected to produce satisfactory performance...
In this paper, a framework for collaborative face recognition from video sequences in a multi-camera environment is proposed. Collaboration between cameras allows for higher recognition performance in both the common and non-common field-of-view (FOV) cases. For the latter, the appearance of an object in a nearby camera is predicted using the last tracked position of the object paired with a time-of-arrival...
Compared to traditional SAR, high-resolution PolSAR not only can provide texture and geometry information, but also can provide polarimetric information, which have been used extensively for various surface features recognition. Traditional methods only based on images characteristics which don't apply to high-resolution PolSAR images interpretation, causing the algorithm redundancy and low recognition...
PolSAR images have been used extensively for various surface features recognition and buildings recognition is an important research topic of PolSAR image interpretation. Traditional methods are only based on PolSAR image characteristics and lack subjective knowledge of human image cognition, making low target recognition rate and algorithm redundancy. To overcome this shortcoming, based on human...
An enormous number of images are currently shared through social networking services such as Facebook. These images usually contain appearance of people and may violate the people's privacy if they are published without permission from each person. To remedy this privacy concern, visual privacy protection, such as blurring, is applied to facial regions of people without permission. However, in addition...
With the rapid development of modern information technology, target recognition plays an increasingly important role in agricultural production, national defense construction. However, the existing target recognition algorithm has many limitations, such as image distortion, difficult to recognize target image or poor recognition results because of camera angles and lighting conditions. Based on the...
Adaptive boosting (AdaBoost) can boost a weak learning algorithm with an accuracy slightly better than random guessing into an arbitrarily accurate strong learning algorithm. It has been applied to target recognition with single feature classifier. However, the poor discriminative power of extremely weak single feature classifier limits its application. In this paper, we present a novel comprehensive...
The difficulties of aircraft type recognition methods are introduced and the necessity of multi-classifier fusion decision method is discussed. The some kinds of invariants: Hu moments, Affine moments, Zernike moments, Wavelet moments, are used for constructing four SVM classifiers. Based on the above four classifiers, an adaptive-weight regularization method is proposed for improving aircraft type...
Polarimetric decomposition techniques have been applied in remote sensing in the area of air-space-borne radar and have achieved much progress in recent years. However, very few apply these polarimetric decomposition techniques to the Ground Penetrating Radar (GPR).We currently apply GPR data sets to characterize and classify the subsurface targets using Pauli decomposition method. The Pauli decomposition...
Tensor linear discriminant analysis (LDA) is an effective feature extraction method for images, but it just considers the globally discriminative information of the data and neglects to preserve the local structure. In this paper, we propose a feature extraction approach based on tensor globally and locally discriminative information preserving projections for SAR target configuration recognition...
The Principal Component Analysis(PCA) is used to aggregate the recognition attribute, in order to decrease the association of each attribute and reduce the attribute. The Neural Networks is used to recognize the target. The use of optimizing policy can improve the constringency speed and the generalization ability of the Neural Networks. The combination of Principal Component Analysis and Neural Networks...
In order to carry on multi target recognition quickly and effectively, according to the characteristics of SIFT, PCASIFT and SURF algorithm, a method of multi target recognition based on SURF algorithm and OpenCV is studied. The method includes multi angles recognition and multi targets recognition. Firstly, feature points were extracted single target or multiple targets by SURF algorithm, then storing...
In this paper, a new recognition algorithm of SAR image which is based on combined templates has been proposed. The new algorithm is based on the traditional mean templates recognition. We use some statistical information of the training samples to make a refusing threshold, which is expected to have the ability that can refuse the non-template-class targets effectively. Meanwhile, the proposed combined...
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