Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Architectural distortions, masses and microcalcifications are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four typ...

The brain is one of the important organs in human body. It controls functions such as vision, hail, memory, knowledge, personality, and difficulty at work. Numerous health associations have rated tumors an alternative major imbalance that causes highest number deaths worldwide. Diagnosis undiagnosed tumor provides opportunity for effective medical treatment. At diagnosis, a shows growth extra c...

In this paper we present a new fusion technique to increase the information content of the fused image. We propose information fusion by maximizing the wavelet entropy using windowing technique. It helps to diagnose the diseases like tumor, cancer ...etc effectively. The images are decomposed by wavelet transform and using maximum selection rule the low frequency and high frequency bands are fu...

This research builds a system for identifying the maturity level of areca fruit based on digital image processing using texture and color features through Gray Level Co-Occurrence Matrix (GLCM) Color moments. The initial stage is pre-processing so that it can be processed to next stage, namely feature extraction. Texture extraction was performed (GLCM), correlation value moments, mean used in t...

As the production speeds of factories increase, it becomes more and challenging to inspect products in real time. The goal this article is come up with a computationally efficient texture discrimination algorithm by first testing their ability localize defects then increase efficiency removing less effective parts them. Therefore, abilities most popular classification algorithms such as GLCM, L...

This Study proposes the approach for crop classification using Grey Level Co-occurrence Matrix feature of Synthetic Aperture Radar (SAR) images. The method utilizes SAR Images acquired by Sentinel 1A Data and extract textural features GLCM. In this study, we investigate potential (GLCM)-based texture information horticulture with images in Kharif cloud weather condition. A study on satellite im...

Monitoring of forests is important for the diagnosis insect damage to vegetation. Detection and monitoring damaged areas facilitates control pests practitioners. For this purpose, Unmanned Aerial Vehicles (UAVs) have been recently used detect areas. In order distinguish from healthy on UAV images, it necessary extract feature parameters images. Therefore, extraction an step in Computer Aided Di...