Morphological image enhancement and segmentation

Terol-Villalobos, Iván R.

doi:10.1016/s1076-5670(01)80106-3

Cited by 22 publications

(12 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand a methodology to enhance contrast based on colour statistics from a training set of images which look visually appealing is presented. Here, the basic idea is to select a set of training images which look good perceptually, next a Gaussian mixture model for the colour distribution in the face region is built, and for any given input image, a colour tone mapping is performed so that the colour statistics in the face region matches the training examples [2], [3], [5]. In this way, even though the reported algorithms to compensate changes in lighting are varied, some are more adequate than others.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of Images Using Morphological Transformations

Sreedhar¹,

Panlal²

2012

IJCSIT

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Enhancement of Images Using Morphological Transformations

Sreedhar¹,

Panlal²

2012

IJCSIT

View full text Add to dashboard Cite

show abstract

“…Often combinations of these operations are used to perform morphological image analysis [3], [17]. Irrespective of the size of the structuring element, the origin is located at its centre.…”

Section: Morphological Operationsmentioning

confidence: 99%

Morphological Transformations for Enhancement of Images with Poor Contrast and Detection of Background

Tekam¹

2015

International Journal of Innovative Research in Electrical, Ele

View full text Add to dashboard Cite

This paper deals with enhancement of images with poor contrast and detection of background. Proposes a frame work which is used to detect the background in images characterized by poor contrast. Image enhancement has been carried out by the two methods based on the Weber"s law notion. The first method employs information from image background analysis by blocks, while the second transformation method utilizes the opening operation, closing operation, which is employed to define the multi-background gray scale images. The complete image processing is done using MATLAB simulation model. Finally, this paper is organized as follows as Morphological transformation and Weber"s law. Image background approximation to the background by means of block analysis in conjunction with transformations that enhance images with poor lighting. The multi background notion is introduced by means of the opening by reconstruction shows a comparison among several techniques to improve contrast in images. Histogram for every method is shown. Finally, conclusions are presented.

show abstract

“…For background detection three methods has been carried out. Other works based on the contrast mapping concept have been developed elsewhere [3]- [5]. Even though morphological contrast has been largely studied, there are no methodologies.…”

Section: Introductionmentioning

confidence: 99%