Showing papers by "Rakesh Mohan published in 1996"

VeggieVision: a produce recognition system

Abstract: The authors present an automatic product 1D system ("VeggieVision"), intended to ease the produce checkout process. The system consists of an integrated scale and imaging system with a user-friendly interface. When a produce item is placed on the scale, an image is taken. A variety of features, color, texture (shape, density), are then extracted. These features are compared to stored "signatures" which were obtained by prior system training (either on-line or off-line). Depending on the certainty of the classification, the final decision is made either by the system or by a human from a number of choices selected by the system. Over 95% of the time, the correct produce classification is in the top four choices.

Text-based search of TV news stories

Abstract: Our goal is to enable viewers to access TV programs based on their content. Towards this end, we present a system that automatically captures and processes TV news programs into a database that can be searched over the internet. Users browse this database by submitting simple English queries. The results of the query is a hyperlinked list of matching news stories. Clicking on any item in the list immediately launches a video of the pertinent part of the news broadcast. We segment TV news broadcasts into distinct news stories. We then index each story as a separate entity. In reply to a query, videos for these news stories are displayed rather than the whole TV program. News program s ar usually accompanied by a transcript in closed caption text. The closed caption text contains markers for story boundaries. Due to the live nature of TV news programs, the closed caption lags the actual audio/video by varying amounts of time up to a few seconds. The closed caption text, thus, has to be shifted to be aligned in time to the video. We use video and audio events to do this synchronization. The closed caption for each story is entered into a database. In response to a query, the database retrieves and ranks the matching closed caption stores. An HTML document is returned to the user which lists: 1) the name and time of the news program that this story belongs to, 2) thumbnails providing a visual summary of the story, 3) closed caption text. To view a news story, the user simply clicks on an item form the list and the video for that story is streamed onto a media player at the user side. This system maintains the manner of presentation of the media, namely video for TV programs, while allowing the common search and selection techniques used on the web.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Size featuring/deciding system for object

Abstract: PROBLEM TO BE SOLVED: To provide a device and a method capable of recognizing and learning the size of an object such as a farm product. SOLUTION: An illumination source for irradiating a screen is provided, the illumination source is controlled and an image processing system obtains the first digital image of the screen provided with the object irradiated at a high level and the second digital image of the object irradiated at a low level. Algorithm is used and an object image is newly area-divided from the background image of the screen by the comparison of the two digital images. The processing image of a round object (usable so as to feature the size of the object) is compared with a stored reference image. When collation is performed, the size of the object is recognized. The processing image of the object of the unrecognized size is stored in a memory based on a specified standard by labelling the actual size of the object and the size of the object is recognized at the time of forming the image in the future. By this system, learning is made possible so as to recognize the size of the object not known beforehand.