Image Search: Efficient Image Retrieval Using Color and Texture Features

Content-based image retrieval using color and texture fused features

A Content Based Image Retrieval System is a computer system for browsing, searching and retrieving images from a large database of digital images .Most common methods of image retrieval utilize some method of adding meta data such as captioning, keywords or description to the images so that retrieval can be performed over the annotation words. Content Based Image Retrieval (CBIR) deals with ret...

Content Based Image Retrieval Using Dominant Color and Texture Features

The purpose of this Paper is to describe our research on different feature extraction and matching techniques in designing a Content Based Image Retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Content Based Image Retrieval (CBIR) is the retrieval of images based on feature...

Content Based Image Retrieval Using Color and Texture Features

Plant Image Retrieval Using Color, Shape and Texture Features

We present a content-based image retrieval system for plant image retrieval, intended especially for the house plant identification problem. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various wellknown color, shape and texture features for this problem, as well as introducing some new text...

Region Filtering Using Color and Texture Features for Image Retrieval

This paper presents a region-based image retrieval (RBIR) system in which users can choose specific regions as the query. Our goal is to assist the user to formulate more precise queries with which the retrieval system can focus on the user’s interested part. In this work, images are partitioned into a set of regions by using the watershed segmentation. Color-size histogram and Gabor texture fe...