Object recognition can be formulated as matching image features to model features. When recognition is based on point feature, feature correspondence should be one-to-one. However, due to noises, repetitive structures...
详细信息
ISBN:
(纸本)9780819469502
Object recognition can be formulated as matching image features to model features. When recognition is based on point feature, feature correspondence should be one-to-one. However, due to noises, repetitive structures and background clutters, features don't match one-to-one but one-to-many. By using the multi-scale feature point technique, we present an object recognition algorithm that makes features match one-to-one. First, it determines the correspondence by using the location, scale factor, orientation and local invariant descriptor of each feature point. then a vote is recorded for the center, scale factor and rotation angle of object for each correspondence point. this approach can recognize the objects in the case of scale change, rotation angle changes and partial occlusion. Experimental results demonstrate the robustness of the overall approach on various image pairs.
In this paper, the main idea is to use the prior knowledge to guide the segmentation. Firstly the continuity among adjacent frames is used to create a motion template according to the Displaced Frame Difference's ...
详细信息
ISBN:
(纸本)9780819469502
In this paper, the main idea is to use the prior knowledge to guide the segmentation. Firstly the continuity among adjacent frames is used to create a motion template according to the Displaced Frame Difference's (DFD) higher character([1]). And then the color template is established by using the k-means clustering. Based upon the information derived from the previous two templates, the segmentation image is defined as foreground, background and boundary regions. then, the segmentation problem is formulated as an energy minimization problem. the hard edge of foreground is then obtained by implementing graph-cut algorithm. Experimental results demonstrate the effectiveness of proposed algorithm.
作者：
Fan, DongjinFeng, JufuPeking Univ
Sch Elect Engn & Comp Sci Dept Machine Intelligence State Key Lab Machine Percept Beijing 100871 Peoples R China
the segmentation of fingerprint images plays an important role in fingerprint recognition. A new algorithm based on Local Fourier Transform (LFT) for the fingerprint segmentation is proposed in this paper. Firstly, we...
详细信息
ISBN:
(纸本)9780819469502
the segmentation of fingerprint images plays an important role in fingerprint recognition. A new algorithm based on Local Fourier Transform (LFT) for the fingerprint segmentation is proposed in this paper. Firstly, we perform the Local Fourier Transform on image to get eight independent Local Fourier coefficients per pixel. then, block features are extracted by calculating the 2(nd), 4(th), 6(th) order moments of the local Fourier coefficients of every pixel in the block. After that, a Fisher linear discriminant classifier is trained for the classification per block. Finally, mathematical morphology and region boundary smoothing is applied as postprocessing to obtain compact clusters and to reduce the number of classification errors. the experimental results on the databases of FVC2004 demonstrate the robustness and the efficiency of the proposed method.
In this paper, an algorithm for hyperspectral image compression is presented. It carries DCT (Discrete Cosine Transform) on spectral bands to exploit the spectral correlation and then DWT (Discrete Wavelet Transform) ...
详细信息
ISBN:
(纸本)9780819469519
In this paper, an algorithm for hyperspectral image compression is presented. It carries DCT (Discrete Cosine Transform) on spectral bands to exploit the spectral correlation and then DWT (Discrete Wavelet Transform) on every eigen image to exploit the spatial correlation. After that. 3D-SPIHT (three-dimensional Set Partitioning in Hierarchical Trees) is performed for encoding. Experiments were done on the OMIS-I(Operational Modular Imaging Spectrometer) image and the performance of this algorithm was compared withthat of 2D-SPIHT. the results show that the performance of 3D-SPIHT based on DCT and DWT is much better than that of 2D-SPIHT and the quality of the reconstructed images is satisfying.
In modem ITS (Intelligent Transportation Systems), the close shot images captured by camera are used to precise recognition of information of vehicles such as VLP (vehicle license plate), VS(vehicle shape), VBC(vehicl...
详细信息
ISBN:
(纸本)9780819469502
In modem ITS (Intelligent Transportation Systems), the close shot images captured by camera are used to precise recognition of information of vehicles such as VLP (vehicle license plate), VS(vehicle shape), VBC(vehicle body color) and etc. the precise recognition of vehicle information seriously depends upon quality of images captured by camera. the assessment of image quality is a meaningful work, which can be used to monitor the working state and adjust the control parameters of camera, further more can guide the recognition of information of vehicle. this paper proposes a novel content-based method of assessing images quality for close shot ones in ITS. the method is objective image quality assessment without reference image, which is point to single image. the assessment includes distortion type and distortion amount. Experiments show the method is valid and robust.
In this paper, we propose an improved particle filter algorithm for real-time tracking a randomly moving target in dynamic environment with a moving monocular camera. For making the tracking task robustly and effectiv...
详细信息
ISBN:
(纸本)9780819469502
In this paper, we propose an improved particle filter algorithm for real-time tracking a randomly moving target in dynamic environment with a moving monocular camera. For making the tracking task robustly and effectively, color histogram based target model is integrated into particle filter algorithm. Bhattacharyya distance is used to weight samples by calculating each sample's histogram with a specified target model and it makes the measurement matching and samples' weight updating more reasonable. In order to reduce sample depletion, the improved algorithm will be able to take the latest observation into account. the experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.
the fusion effect on the high-resolution remote sensing image using the traditional fusion technique such as Principal Component Analysis(PCA), is not satisfying. Considering the well-developed technique of Minimum No...
详细信息
ISBN:
(纸本)9780819469519
the fusion effect on the high-resolution remote sensing image using the traditional fusion technique such as Principal Component Analysis(PCA), is not satisfying. Considering the well-developed technique of Minimum Noise Fraction(MNF) transform and the flexible ability of Wavelet transform, a new fusion method (MNFWT) integrating MNF and Wavelet transform was studied using multi-spectral (MS) IKONOS image at 4-m spatial resolution and panchromatic (PAN) IKONOS image at 1-m resolution. Compared with PCA fusion method, MNFWT approach performs more efficiently both in improving the spatial information and preserving the spectral information.
A novel feature descriptor - contourlet Fourier invariant feature, which combine contourlet decomposition and Fourier transforms and is translation-, rotation-, and scale-invariant, is put forward in this paper. First...
详细信息
ISBN:
(纸本)9780819469502
A novel feature descriptor - contourlet Fourier invariant feature, which combine contourlet decomposition and Fourier transforms and is translation-, rotation-, and scale-invariant, is put forward in this paper. Firstly, the translation and rotation invariant are achieved by Fourier transform along the circles that around the mass center of the scale-normalized target. then statistic parameters of General Gaussian density (GGD) model of each contourlet sub-bands are evaluated. GGD parameters and contourlet decomposition coefficients are both as the features, which not only with rotation, shift and scaling invariant, but also withthe contourlet inherent property of multi-resolution, local and multi-direction. We present experimental results using this descriptor in infrared imagerecognition, and it shows this descriptor is a good choice for object recognition.
In this paper, a new image fusion frame based on nonsubsampled contourlet transformation is provided. In this frame, a new method based on the local correlation coefficients is explored, the experiment results of this...
详细信息
ISBN:
(纸本)9780819469519
In this paper, a new image fusion frame based on nonsubsampled contourlet transformation is provided. In this frame, a new method based on the local correlation coefficients is explored, the experiment results of this method can obtain relatively high spatial resolution and preserve high spectral resolution.
Since Chavez proposed the highpass filtering procedure to fuse multispectral and panchromatic images, several fusion methods have been developed based on the same principle: to extract from the panchromatic image spat...
详细信息
ISBN:
(纸本)9780819469519
Since Chavez proposed the highpass filtering procedure to fuse multispectral and panchromatic images, several fusion methods have been developed based on the same principle: to extract from the panchromatic image spatial detail information to later inject it into the multispectral one. In this paper, we present new fusion alternatives based on the same concept. using the multiresolution contourlet decomposition to execute the detail extraction phase and the generalized intensity-hue-saturation (GIHS) and principal component analysis (PCA) procedures to inject the spatial detail of the panchromatic image into the multispectral one. Experimental results show the new fusion method have better performance than GIHS, PCA, wavelet and the method of improved GINS and PCA mergers based on wavelet decomposition.
暂无评论