Image retrieval based on color, texture and shape is an emerging and wide area of research scope. In this paper we present a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency using dominant color feature. The image and its complement are partitioned into non-overlapping tiles of equal size. The features drawn from cond...

Image retrieval based on color, texture and shape is an emerging and wide area of research scope. In this paper we present a novel framework for combining all the three i.e. color, texture and shape information, and achieve higher retrieval efficiency using dominant color feature. The image and its complement are partitioned into non-overlapping tiles of equal size. The features drawn from cond...

Abstract—The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haa...

In this paper, we proposed a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of ...

This paper presents a novel method to grade the date fruits based on the combination of shape and texture features. The method begins with reducing the specular reflection and small noise using a bilateral filter. Threshold based segmentation is performed for background removal and fruit part selection from the given image. Shape features is extracted using the contour of the date fruit and tex...