Massachusetts Institute of Technology

Other

Inscripta, Inc.

Landrex Technologies Co., Ltd.

Pawan Sinha

Pamela R Lipson

Keith Raymond Kluender

Tomaso A Poggio

Chukka Srinivas

W Eric Grimson

W Eric L Grimson

Michael Oren

Aparna Ratan

Constatine P Papageorgiou

An image search and retrieval system and method of operation within such a system are disclosed. The image search and retrieval system includes a search engine coupled to an image analyzer, an input system, an output system and an image database. The image search and retrieval system includes one or more feature modules which define particular regions of an image and particular measurements to make on pixels within the define image region as well as the measurements to make on neighboring pixels in neighboring image regions for a given application and communicate this application specific information to the image analyzer thereby allowing rapid comparisons of images.

Information search and retrieval system

The invention relates to using VLSI techniques to store information on a substrate. One embodiment of a die with text deposited upon the die uses semiconductor processing techniques during fabrication. Included in the die are a substrate, a first paragraph and a second paragraph. The first and second paragraphs are in contact with the substrate. The second paragraph is aligned with the first paragraph in a column.

VLSI-based system for durable high-density information storage

An inspection system includes a plurality of models are applied in a way that enhances the effectiveness of each type of model. In one embodiment, a printed circuit board inspection system includes an image model, a structural model and a geometric model to inspect objects. The image model is first applied to an object being inspected to identify objects which look alike. After the image model is applied, a structural model is applied to determine whether the object exists in the image that has the same structure and is used to decide if the image model has truly found a part in the image. Lastly, a geometric model is applied and uses the approximate positional data provided by the previous two models to determine precisely the location of the object being inspected. Also described are techniques for learning and updating the plurality of models.

Image processing system for use with inspection systems

An image search and retrieval system and method of operation within such a system are disclosed. The image search and retrieval system includes a search engine coupled to an image analyzer, an input system, an output system and an image database. The image search and retrieval system includes one or more feature modules which define particular regions of an image and particular measurements to make on pixels within the defined image region as well as the measurements to make on neighboring pixels in neighboring image regions for a given application and communicate this application specific information to the image analyzer thereby allowing rapid comparisons of images.

An image processing system for generating a class model from an image by identifying relative relationships between different properties of different image regions, includes a region partitioner a relationship processor, a template generator and an image detector. The image processing system utilizes a class model defined by one or more relative relationships between a plurality of image patches. The relative relationships describe the overall organization of images within an image class. The relative relationships are encoded in a global deformable template which can be used to classify or detect images. The class model may be pre-defined or generated by the image processing system. In one embodiment, the class model is generated from a low resolution image.

Method and apparatus for classifying and identifying images

A trainable object detection system and technique for detecting objects such as people in static or video images of cluttered scenes is described. The described system and technique can be used to detect highly non-rigid objects with a high degree of variability in size, shape, color, and texture. The system learns from examples and does not rely on any a priori (hand-crafted) models or on motion. The technique utilizes a wavelet template that defines the shape of an object in terms of a subset of the wavelet coefficients of the image. It is invariant to changes in color and texture and can be used to robustly define a rich and complex class of objects such as people. The invariant properties and computational efficiency of the wavelet template make it an effective tool for object detection.

Trainable system to search for objects in images

Miniature tablet

An image processing system and methods of operation within such a system are disclosed. The image processing system utilizes a class model defined by one or more relative relationships between a plurality of image patches. The relative relationships describe the overall organization of images within an image class. The relative relationships are encoded in a global deformable template which can be used to classify or detect images. The class model may be predefined or generated by an image processing system.

Growing community of inventors

Cambridge, MA, United States of America

Pawan Sinha