In this paper we show how the distance functions generated by neighborhood sequences provides flexibility in image processing algorithms and image database retrieval. Accordingly, we present methods for indexing and segmenting color images, where we use digital distance functions generated by neighborhood sequences to measure distance between colors. Moreover, we explain the usability of neighb...

Image retrieval is a very imperative area of digital image processing. Images can be retrieving from a large database on the basis of text, color, structure or content. Content-based image retrieval uses the visual fillings of an image such as texture, color, shape, & spatial layout to represent and index the image. In typical CBIR systems, the visual content of the pictures in the database are...

We address the problem of fusing colour information for face authentication. The performance of a face verification system in different colour spaces is experimentally studied first. The verification process is based on the normalised correlation measure within the LDA feature space. The confidence level of the measurement made is then calculated for each colour subspace. Confidence measures ar...

This paper presents a technique in classifying the images into a number of classes or clusters desired by means of Self Organizing Map (SOM) Artificial Neural Network method. A number of 250 color images to be classified as previously done some processing, such as RGB to grayscale color conversion, color histogram, feature vector selection, and then classifying by the SOM Feature vector selecti...

Content based image retrieval (CBIR) from large resources has become a dominant research field and found wide interest nowadays in many applications. In this thesis work, we design and implement a content based image retrieval system that uses color and texture as visual features to describe the content of an image region. We use k-nearest neighbor (knn) and HSV color model to extract feature o...

breast cancer is the second largest cause of cancer deaths among women. at the same time, it is also among the most curable cancer types if it can be diagnosed early. this paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. the proposed method includes three main modules: the feature extraction module, the classifier module and the optimization module. in t...

the problem of automatic signature recognition has received little attention incomparison with the problem of signature verification, despite its potentialapplications for many business processes and can be used effectively in paperlessoffice projects. this paper presents model-based off-line signature recognition withrotation invariant features. non-linear rotation of signature patterns is one...

The work investigates the use of multi dimensional histograms for segmentation of images of chronic wounds. We employ a Support Vector Machine (SVM) classifier for automatic extraction of wound region from an image. We show that the SVM classifier can generalize well on the difficult wound segmentation problem using only 3-D dimensional color histograms. We also show that color histograms of hi...

Target object detection in aerial surveillance using image processing techniques is growing more and more important. Aerial surveillance is more suitable for monitoring fast moving targets and covers a much larger spatial area. These technologies have a variety of applications, such as traffic management, police and military. Aerial view has the advantage of providing a better perspective of th...