Digital image processing
Structure of Computers and Computations
Structure of Computers and Computations
Local Properties of Binary Images in Two Dimensions
IEEE Transactions on Computers
Feature Extraction by Golay Hexagonal Pattern Transforms
IEEE Transactions on Computers
IEEE Transactions on Computers
A Parallel Picture Processing Machine
IEEE Transactions on Computers
A computer oriented toward spatial problems
IRE-ACM-AIEE '58 (Western) Proceedings of the May 6-8, 1958, western joint computer conference: contrasts in computers
Sorting networks and their applications
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
PUMPS Architecture for Pattern Analysis and Image Database Management
IEEE Transactions on Computers
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One of the more complex processing problems facing both the military and commercial world is that of image analysis and understanding. The range of applications in which a real time computer vision system could have impact is extraordinarily large. In the military arena the need and potential benefits of a real time capability for target acquisition, autonomous guidance and image interpretation are well recognized and understood. To this end the Department of Defense is currently supporting several projects such as the DARPA Image Understanding (I.U.) Program to analyze both the processing requirements and machine organization for complex image processing and analysis. Truly autonomous systems which can perform both the imaging and processing in real-time using inexpensive and compact hardware will have significant impact in the tactical scenario for applications requiring remote sensing and analysis. (The term 'smart-sensors' has been introduced for hardware which performs both the sensing and processing in a single substrate.) In addition, an equally important impact might be made in areas such as automated production and inspection for machine assembly, etc. These two general areas are in many ways analogous and much of the hardware and software developed can be applied to both problems. Significant differences do, however, exist in terms of the signal to noise specification of the images, the required response time of the machinery, and the system constraints such as machine size and cost.