A detection system based on digital image processing and machine learning classification was developed to detect normal cancerous lung conditions. 340 data from LIDC –IDRI were processed through several stages. The first stage is pre-processing using three filter variations contrast stretching, which reduce noise increase contrast. segmentation process uses Otsu Thresholding clarify the ROI of ...

This paper presents a novel content based image retrieval (CBIR) system based on Framelet Transform combined with gray level co-occurrence matrix (GLCM).The proposed method is shift invariant which captured edge information more accurately than conventional transform domain methods as well as able to handle images of arbitrary size. Current system uses texture as a visual content for feature ex...

Abstract This paper studies the tracking of wooden veneer sheets by matching their respective wet and dry colour images. The has proved to be a challenging task due random mutations during processing in terms color changes, emergence defects, and, occasionally, lost pieces surface. proposed procedure involves image segmentation with five different sizes, followed segment-wise extraction Gray Le...