LBP features for breast cancer detection

Classification of Breast cancer Using Local Binary Pattern and Gabor Filter

“…As shown in fig.1, the input image is composed of the background and breast region. This background part gets eliminated in preprocessing [4]. …”

“…It is believed that the texture plays an important role in the visual system for recognition and interpretation of data. Local binary pattern [4], [7], [9], [10] and Gabor filter is used in proposed system to extract the texture features from the processed image.…”

A Survey of Breast Cancer Detection and Classification Based on Texture Feature

“…Caberrera et al [2] DDSM database Texture feature Highly dependent on a reference gray level Pavelkral et al [4] DDSM and MIAS database LBP features Accuracy achieved -84%…”

“…However, the study proposed is highly dependent on an adequate value of the reference gray level to achieve a successful segmentation and extraction of the suspicious region. Pavel kral et al [4] proposes a method for breast cancer detection at an early stage, using LBP features. The background image and breast image is separated using Otsu method.…”

“…The image preprocessing include image enhancement, removal of noise and breast part extraction. Smoothing image pixel using averaging filter [5], Otsu method [4] to separate background from breast region, morphological operations [6], [11], sharpening [2] have been used for preprocessing on digital mammographic images.…”