Content-based image retrieval (CBIR) is the retrieval of images from a collection by means of internal feature measures of the information content of the images. In CBIR systems, text media is usually used only to retrieve exemplar images for further searching by image feature content. This research work describes a new method for integrating multimedia text and image content features to increase the retrieval performance of the system. I am exploring the content-based features of an image extracted from a video to build a storyboard for search retrieval of images. Metadata encoded multimedia features include extracting primitive features like color, shape and text from an image. Histograms are built for all the features extracted and stored in a database. Images are searched based on comparing these histogram values of the extracted image with the stored values. These histogram values are used for extraction of keyframes from a collection of images parsed from a video file. Individual shots of images are extracted from a video clip and run through processes that extract the features and build the histogram values. A keyframe extraction algorithm is run to get the keyframes from the collection of images to build a storyboard of images. In …

Through my work, I explored the application of texture and materials as a means to identify specific functions. I show how texture and material selections that specifically engage the sense of touch can aid in effective environments for the elderly. By means of this study, I demonstrated how the sensory perception of the elderly is utilized in designing productive environments for the senior population in regards to the sense of touch. The interior design of senior living environments can greatly enhance the retirement experience for the elderly population. With the information I have gained through my research and work will reflect in my future design projects. I also wish to share this enlightenment with others in my field of study.