EPAComp: An Architectural Model for EPA Composition
Luís Henrique Neves Villaça, Sean Wolfgand Matsui Siqueira, et al.
SBSI 2023
In this paper we deal with the problem of detecting and segmenting objects in textured dark-field digital imagery for automated visual-inspection applications. We first present a technique for correcting optical shading effects in conventional dark-field microscopy. After compensating for possible imperfections in the optical setting we address the problem of segmenting objects (defects) in textured dark-field images. The technique that we will follow is based on a sequential application of local operators, which serves the purpose of clustering the object and the background gray levels. This procedure can be considered an extension of average-thresholding-type techniques. Both algorithms for shading correction and object segmentation have fast implementations in general-purpose image-processing pipeline architectures, and therefore they are appealing to real-time computer vision applications. Computational examples showing the appropriateness of the shading-correction procedure as well as the effectiveness of the segmentation wil be discussed. © 1985 Optical Society of America.
Luís Henrique Neves Villaça, Sean Wolfgand Matsui Siqueira, et al.
SBSI 2023
Minerva M. Yeung, Fred Mintzer
ICIP 1997
Upendra Sharma, Prashant Shenoy, et al.
ICCAC 2013
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding