Diabetes mellitus (DM) and its cause’s diabetic retinopathy (DR) are major health problems. To combat this approaching epidemic, proposes a noninvasive automated method to detect DM and NPDR by distinguishing Healthy/DM and NPDR/DM sans NPDR (DM without NPDR) samples using an array of tongue features consisting of color, texture, and geometry. The various tongue features like color, texture, an...

We investigate the extraction of effective color features for a content-based image retrieval (CBIR) application in dermatology. Effectiveness is measured by the rate of correct retrieval of images from four color classes of skin lesions. We employ and compare two different methods to learn favorable feature representations for this special application: limited rankmatrix learning vector quanti...

In this paper, we present a new and effective color image retrieval scheme for combining all the three i.e. color, texture and shape information, which achieved higher retrieval efficiency. Firstly, the image is predetermined by using fast color quantization algorithm with clusters merging, and then a small number of dominant colors and their percentages can be obtained. Secondly, the spatial t...

In this paper suggests to define 20 facial features being used in practical program and the method of extraction of 20 facial features from 2D image. The experimental image is to be restricted to input one person's image, background of the image can be taken in anywhere, the lighting condition is not uniform, and there is no racial restriction. The suggested method is to seek facial candidate r...

This paper presents our research in image content based indexing and retrieval, a key technology in digital image libraries. In most of the existing image content-based techniques, image features used for indexing and retrieval are global, features are computed over the entire image. The major problem with the global image feature based retrieval methods is that background features can be easil...

The development of a new object-based image retrieval (OBIR) engine is discussed. Its goal was to yield intuitive results for users by using human-based techniques. The engine utilizes a unique and efficient set of 15 features: 11 color categories and 4 texture features, derived from the color correlogram. These features were calculated for the center object of the images, which was determined ...

Extending differential-based operations to color images is hindered by the multi-channel nature of color images. The derivatives in different channels can point in opposite directions, hence cancellation might occur by simple addition. The solution to this problem is given by the structure tensor for which opposing vectors reinforce each other. We review the set of existing tensor based feature...

A segmentation-based fully-polarimetric synthetic aperture radar (PolSAR) image classification method that incorporates texture features and color features is designed and implemented. This method is based on the framework that conjunctively uses statistical region merging (SRM) for segmentation and support vector machine (SVM) for classification. In the segmentation step, we propose an improve...

Nowadays, problem of shape and texture for 3D retrieval is still a challenge research. Although several methods exist, but we still have a space to improve the performance. In this paper, we aim to improve our previous 3D shape features and inserting texture features. We first do pose normalization as a process of adjusting the size, location, and orientation of a given object in a canonical sp...

  Context: In recent years, nanotechnology has opened up several new avenues of extraordinary biomedical potential by modulating metals into their nanosize leading to significant improvement in their chemical, physical and optical properties. Introduction: <span style="color...