A Multiscale Stochastic Image Model for Automated Inspection - Image Processing, IEEE Transactions on
نویسندگان
چکیده
In this paper, we develop a novel multiscale stochastic image model to describe the appearance of a complex threedimensional object in a two-dimensional monochrome image. This formal image model is used in conjunction with Bayesian estimation techniques to perform automated inspection. The model is based on a stochastic tree structure in which each node is an important subassembly of the three-dimensional object. The data associated with each node or subassembly is modeled in a wavelet domain. We use a fast multiscale search technique to compute the sequential MAP (SMAP) estimate of the unknown position, scale factor, and 2-D rotation for each subassembly. The search is carried out in a manner similar to a sequential likelihood ratio test, where the process advances in scale rather than time. The results of this search determine whether or not the object passes inspection. A similar search is used in conjunction with the EM algorithm to estimate the model parameters for a given object from a set of training images. The performance of the algorithm is demonstrated on two different real assemblies.
منابع مشابه
A multiscale stochastic image model for automated inspection
We develop a novel multiscale stochastic image model to describe the appearance of a complex three-dimensional object in a two-dimensional monochrome image. This formal image model is used in conjunction with Bayesian estimation techniques to perform automated inspection. The model is based on a stochastic tree structure in which each node is an important subassembly of the three-dimensional ob...
متن کاملTexture synthesis via a noncausal nonparametric multiscale Markov random field
Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesizing and capturing the characteristics of a wide variety of textures, from the highly structured to the stochastic. We use a multiscale synthesis algorithm incorporating local annealing to obtain larger realizations of texture visually indistinguishable from the training texture.
متن کاملAutomatic road crack detection and classification using image processing techniques, machine learning and integrated models in urban areas: A novel image binarization technique
The quality of the road pavement has always been one of the major concerns for governments around the world. Cracks in the asphalt are one of the most common road tensions that generally threaten the safety of roads and highways. In recent years, automated inspection methods such as image and video processing have been considered due to the high cost and error of manual metho...
متن کاملAutomatic Detection and Localization of Surface Cracks in Continuously Cast Hot Steel Slabs Using Digital Image Analysis Techniques
Quality inspection is an indispensable part of modern industrial manufacturing. Steel as a major industry requires constant surveillance and supervision through its various stages of production. Continuous casting is a critical step in the steel manufacturing process in which molten steel is solidified into a semi-finished product called slab. Once the slab is released from the casting unit, th...
متن کاملAn overlapping tree approach to multiscale stochastic modeling and estimation
Recently, a class of multiscale stochastic models has been introduced in which random processes and fields are described by scale-recursive dynamic trees. A major advantage of this framework is that it leads to an extremely efficient, statistically optimal algorithm for least-squares estimation. In certain applications, however, estimates based on the types of multiscale models previously propo...
متن کامل