In this paper, we present a comprehensive model that predicts reflectance from rough diffuse surfaces. We show that diffuse reflectance from rough surfaces increases as the viewing direction approaches the source dire...
详细信息
ISBN:
(纸本)0818638826
In this paper, we present a comprehensive model that predicts reflectance from rough diffuse surfaces. We show that diffuse reflectance from rough surfaces increases as the viewing direction approaches the source direction. This is in contrast to Lambertian surfaces, where radiance is independent on the viewing direction. The new model is a generalization of the Lambertian model, and has significant implications for machine vision, graphics, and remotesensing.
We describe here a knowledge-based system, NEXSYS (Nextwork EXtraction SYStem) which was designed for the recognition of communication networks in SPOT satellite images. NEXSYS is a frame-based system and uses a co-op...
详细信息
ISBN:
(纸本)0819412384
We describe here a knowledge-based system, NEXSYS (Nextwork EXtraction SYStem) which was designed for the recognition of communication networks in SPOT satellite images. NEXSYS is a frame-based system and uses a co-operative and distributed structure based on a blackboard architecture. Communication networks in SPOT images are composed of thin linear segments. Segments are extracted using mathematical morphology and a Hough transform. An intermediate image representation composed of geometric primitives is obtained. Then an expert module is able to process the segments at the symbolic level trying to recognize networks.
Methods of patternrecognition by digital processing are applied to analyze edges, lines, density of lines, and the standard deviations of pixel brightness of some satellite images in Asian Island Arcs. In South Kyush...
详细信息
ISBN:
(纸本)0780312406
Methods of patternrecognition by digital processing are applied to analyze edges, lines, density of lines, and the standard deviations of pixel brightness of some satellite images in Asian Island Arcs. In South Kyushu where huge activity of younger volcanics occurs from Tertiary to present age, Mt. Takakuma is composed of Miocene granite surrounded by Cretaceous to Quaternary sediments in about 20 km times 20 km square area (Fig. 1). Peripheral area of the Granite includes some gold-bearing tungsten deposits that have been already mined out. Edges and lines extracted in image mostly coincide to the geodynamic fracture system including faults, joints, cracks, and sedimentary stratification. The directional frequencies of the lines are well concordant to the observed major faults. Composite image coincides to the pattern of formations. The heavily vegetated areas can be classified geologically using our method.
Contrast enhancement is one of the fundamental techniques in the processing chain for improving the quality of an image, which is under- or overexposed. The existing enhancement methods are often used in an interactiv...
详细信息
ISBN:
(纸本)0819411973
Contrast enhancement is one of the fundamental techniques in the processing chain for improving the quality of an image, which is under- or overexposed. The existing enhancement methods are often used in an interactive manner which supposes a subjective choice of these methods and of the parameters on which they depend. We have therefore developed a method which allows the automatic enhancement of images by introducing decisional criteria for the choice of the adapted transfer function. The decisional criteria are based on the dynamics and the first two statistical moments of the histogram of the image to be processed.
The publication contains 53 papers. Topics discussed include imaging techniques, signal processing, imageprocessing, signal filtering and prediction, speckle, ultrasonic applications, sonar, patternrecognition, medi...
详细信息
The publication contains 53 papers. Topics discussed include imaging techniques, signal processing, imageprocessing, signal filtering and prediction, speckle, ultrasonic applications, sonar, patternrecognition, medical applications, image reconstruction, acoustic waves, tomography and microscopy.
The task of detection of specific buried objects in ground penetrating radar (GPR) images is considered. A modification of the Hough transform (HT) is proposed and applied to this problem. Methods of texture analysis ...
详细信息
ISBN:
(纸本)0780312406
The task of detection of specific buried objects in ground penetrating radar (GPR) images is considered. A modification of the Hough transform (HT) is proposed and applied to this problem. Methods of texture analysis are used to determine the soil structure. The possibility of gaining information about the material of the buried object is examined. The results of some experiments with GPR imagery are shown and discussed.
Shape features characterizing patterns represented by their distance transform are illustrated. The role they can play in pattern decomposition is described with reference to a process based on the detection of a numb...
详细信息
ISBN:
(纸本)0819413259
Shape features characterizing patterns represented by their distance transform are illustrated. The role they can play in pattern decomposition is described with reference to a process based on the detection of a number of pixels significant for shape interpretation. Suitable sets of these pixels are regarded as feature sets, and used as seeds to be expanded into regions. After a merging phase, the regions originate a meaningful decomposition.
For the image understanding and patten recognitions, it is important to extract invariant features from given images corresponding to various transformations. Once the invariant features are obtained, we can estimate ...
详细信息
ISBN:
(纸本)0819413259
For the image understanding and patten recognitions, it is important to extract invariant features from given images corresponding to various transformations. Once the invariant features are obtained, we can estimate motion parameters and/or categorize objects into equivalent classes based on some criterions. So many techniques to extract invariant features are proposed, and most of them need exact matching between an image before transformation and another image after transformation. But this matching process is not easy to perform. Then we propose a group theoretical method, which does not require a matching process. In this paper, we show the bases of the representation of the perspective projected motion group and those of the spherical projected motion group explicitly.
In this paper, we study patternrecognition using Probabilistic Iterated Function Systems (PIFS). A learning system can be defined by three rules: the encoding rule, the rule of internal change, and the quantization r...
详细信息
ISBN:
(纸本)0819413259
In this paper, we study patternrecognition using Probabilistic Iterated Function Systems (PIFS). A learning system can be defined by three rules: the encoding rule, the rule of internal change, and the quantization rule. In our system, the data encoding is to store an image in a stable distribution of a PIFS. Given an input image f (epsilon) F, one can find a PIFS t (epsilon) T such that the equilibrium distribution of this PIFS is the given image f. Therefore, the input image, f, is encoded into a specification of a PIFS, t. This mapping from F (image space) to T (parameter space of PIFS) defines fractal transformation. Fractal transformation encodes an input image into a relatively small vector which catches the characteristics of the input vector. The internal space T is the parameter space of PIFS. The internal change rule of our system uses a local minima algorithm to encode the input data. The output data of the encoding stage is a specification of a stochastic dynamical system. The quantization rule divides the internal data space T by sample data.
Research in the last decade emphasized the potential of designing adaptive patternrecognition classifiers based on algorithms using multi-layered artificial neural nets. The greatest potential in such endeavors was a...
详细信息
ISBN:
(纸本)0819413267
Research in the last decade emphasized the potential of designing adaptive patternrecognition classifiers based on algorithms using multi-layered artificial neural nets. The greatest potential in such endeavors was anticipated to be not only in the adaptivity but also in the high-speed processing through massively parallel VLSI implementation and optical computing. Computational advantages of such algorithms have been demonstrated in a number of papers. Neural networks particularly the self-organizing types have been found quite suitable crisp pattern for clustering of unlabeled datasets. The generalization of Kohonen-type learning vector quantization (LVQ) clustering algorithm to fuzzy LVQ clustering algorithm and its equivalence to fuzzy c-means has been clearly demonstrated recently. On the other hand, Carpenter/Grossberg's ART-type self organizing neural networks have been modified to perform fuzzy clustering by a number of researches in the past few years. The performance of such neuro-fuzzy models in clustering unlabeled data patterns is addressed in this paper. A recent development of a new similarity measure and a new learning rule for updating the centroid of the winning cluster in a fuzzy ART-type neural network is also described. The capability of the above neuro-fuzzy model in better partitioning of datasets into clusters of any shape is demonstrated.
暂无评论