Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images

• Main Author: Baharom, Mohamad Shahrul Affendi
• Format: Thesis
• Language: English
• Published: 2019
• Subjects: T Technology; TK Electrical Engineering. Electronics. Nuclear Engineering
• Online Access: http://eprints.usm.my/51558/1/Modified%20Piecewise%20Linear%20Mapping%20Contrast%20Enhancement%20And%20Local%20Otsu%20Segmentation%20Methods%20For%20Hep-2%20Cell%20Images.pdf; http://eprints.usm.my/51558/
• Institution: Universiti Sains Malaysia

Indirect Immunofluorescence (IIF) image analysis for classification of Human Epithelial (HEp-2) immunofluorescence patterns is an effective way to identify the presence of Anti- Nuclear Antibody (ANA). Most existing works focussed on HEp-2 cell classification and very few efforts have been dedicated to study the importance of the pre-processing and segmentation techniques. This study analyses the importance of both methods, which could possibly improve the HEP-2 classification process. The pre-processing is capable to provide a better quality cell features in an image through contrast enhancement process, while segmentation which segregates important features could improve the classification performances. This dissertation presents a Modified Piecewise Linear Mapping and Local Otsu Segmentation as a pre-processing and segmentation approach for the HEp-2 images. Proposed pre-processing focus on minimizing the existence of noise in the background and stretching the cell’s contrast by using piecewise linear mapping function technique. Then the process continues with segmentation process, which introduce a new local Otsu segmentation. This method is a combination of Otsu algorithm and morphological operation (including morphological watershed). This stage perform a segregation process to isolate an important information and distinguish an unwanted information about HEp-2 cell in the image. According to the qualitative and quantitative analysis, proposed preprocessing method is able to enhance the contrast and at the same time minimize the existences of the noise. However, some of the image suffers from texture’s cell loss. On the other hand, the proposed segmentation method capable to segment cell and isolate most of the combined cell. But, some structure of unnecessary cell accidently be removed such as small cell or damaged cell. As a conclusion, although there are some losses in cell information, both methods were successful in enhancing the quality of the HEp-2 image and highlighting important cell information.