The aim of this paper is to review existing approaches of preprocessing in mammographic images. The objective of preprocessing is to improve the quality of the image and make it ready for further processing by removing the irrelevant noise and unwanted parts in the background of the mammogram. There are different of methods of preprocessing a mammogram image. Their advantages and disadvantages ...

Image processing has become an active research topic in recent years. Researchers have focused on developing an algorithm using image processing to detect the different types of cancer in its early stage. Various preprocessing steps using image processing have been proposed. But high accuracy, sensitivity and specificity are important. To achieve this, preprocessing of the acquired original ima...

The detection of embedded object from ground penetrating radar GPR imagery is our goal. The GPR image is a cross sectional slices. The embedded objects are metal and/or plastic type. This research has many real world applications such as remote sensing, geology, medicine and civil. The proposed method starts with two dimensional 2D image preprocessing for each slice. The preprocessing involves ...

Optical character recognition (OCR) is one of the most successful application of pattern recognition and image processing. Character geometry is one of the most useful feature for identifying characters in images. The geometric feature extraction techniques proposed in literature are complex and requires extensive effort in implementation. In this paper, we propose a preprocessing technique whi...

texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...

The aim of the project is to detect and classify the brain tumor from MRI image. This project involves mainly 6 stages namely Input Image, Preprocessing, Segmentation, Post Processing, Feature Extraction and Classification. In this phase, 4 stages are implemented, Input image, preprocessing, segmentation and post processing. Input image reads the MRI brain image. Preprocessing mainly includes i...

The FPGA-based image classification accelerator has achieved success in many practical applications. However, most accelerators focus on solving the problem of convolution computation efficiency. End-to-end involves non-convolutional operations, which can also become performance bottlenecks. Therefore, authors propose an JPEG preprocessing accelerator, accelerate non-convolution operations befo...