Title :
Thresholding using an illumination model
Author :
Parker, J.R. ; Jennings, C. ; Salkauskas, A.G.
Author_Institution :
Calgary Univ., Alta., Canada
Abstract :
Most grey-level thresholding methods produce good results in situations where the illumination gradient in the original raster image is regular and not too large. In other cases, such as a large linear change in illumination, a satisfactory bi-level image cannot be produced. If the object pixels can be identified in a variety of positions throughout the image, these can be used to construct a surface whose height is related to illumination at each pixel. This estimate can be used to produce a threshold for each pixel. The method described here uses the Shen-Castan edge detector to identify object pixels, and creates a surface using a moving least squares method that can be used to threshold the image
Keywords :
edge detection; feature extraction; image segmentation; least mean squares methods; lighting; Shen-Castan edge detector; bi-level image; grey-level thresholding methods; illumination gradient; illumination model; moving least squares method; object pixels; raster image; Computer science; Data mining; Detectors; Frequency; Image edge detection; Least squares methods; Lighting; Mathematics; Object detection; Pixel;
Conference_Titel :
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location :
Tsukuba Science City
Print_ISBN :
0-8186-4960-7
DOI :
10.1109/ICDAR.1993.395734