This thesis is concerned with the problem of how to outline regions of interest in medical images, when the boundaries are weak or ambiguous and the region shapes are irregular. The focus on machine learning and interactivity leads to a common theme of the need to balance conflicting requirements. First, any machine learning method must strike a balance between how much it can learn and how wel...

Localized Content based image retrieval is an effective technique for image retrieval in large databases. It is the retrieval of images based on visual features such as color, texture and shape. In this paper, our desired content of an image is not holistic, but is localized. Specifically, we define Localized Content-Based Image Retrieval, where the user is only interested in a portion of the i...

Content Based Image Retrieval (CBIR) is now a widely investigated issue that aims at allowing users of multimedia information systems to automatically retrieve images coherent with a sample image. A way to achieve this goal is the computation of image features such as the color, texture, shape, and position of objects within images, and the use of those features as query terms. We propose to us...

A content-based image retrieval algorithm is proposed after researching feature extraction of image texture, shape feature extraction and relevance feedback algorithm. Fourier transform is used in the feature extraction of the texture. Boundary moments to detect the image boundaries is used in the feature extraction of the shape, similarity measuring function is used in image similarity match. ...

We investigate the potential of foot biometric features based on geometry, shape and texture and present algorithms for a prototype rotation invariant verification system. An introduction to origins and fields of application for footprint-based personal recognition is accompanied by a comparison with traditional hand biometry systems. Image enhancement and feature extraction steps emphasizing o...

OBJECTIVES This paper proposes a measurement method to quantify the abnormal characteristics of the broken parts of ribs using local texture and shape features in chest radiographs. METHODS OUR MEASUREMENT METHOD COMPRISES TWO STEPS: a measurement area assignment and sampling step using a spline curve and sampling lines orthogonal to the spline curve, and a fracture-ness measurement step with...

In modern visual information retrieval systems, visual content is directly addressed by features such as color, texture, shape and spatial relationship. While a large work is being done around the perceptual soundness of models and around the automatic extraction of features, only a limited attention is placed on the combination of useful representations and similarity models with efficient ind...

Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...

In this paper, we present a novel approach for image retrieval based on extraction of low level features using techniques such as Directional Binary Code (DBC), Haar Wavelet transform and Histogram of Oriented Gradients (HOG). The DBC texture descriptor captures the spatial relationship between any pair of neighbourhood pixels in a local region along a given direction, while Local Binary Patter...