Identification of Plants Using Neural Network Technology

Period of Performance: 04/15/1998 - 03/31/1999

Unknown

Phase 2 SBIR

Recipient Firm

Netrologic, Inc.
5080 Shorehame Pl, STE 201
San Diego, CA 92122
Principal Investigator

Abstract

LONG-TERM OBJECTIVES 1. Develop a computerized system, based on hierarchical neural network pattern recognition technology, for reliable identification of plants. 2. Identify poisonous plants. 3. Expedite discovery of new medicinal plants. 4. Create an image database directly from plant material and link with existing medicinal plant databases. 5. Develop commercial product for pharmaceutical companies, agriculture and others. SPECIFIC AIMS 1. Design hierarchical system of neural networks to follow natural plant taxonomy groupings and extend our identification technology to a large number of plant species. 2. Improve accuracy of identification. 3. Design a prototype workstation for botanical and agricultural field stations and laboratories. RESEARCH DESIGN AND METHODS FOR ACHIEVING GOALS. 1. Digitize large number of plant species from special collections. 2. Measure automatically venation patterns and shape. 3. Design hierarchical neural networks to divide plants into natural groupings. 4. Accumulate virtual herbarium database as leaves are digitized (scanned or photographed). POTENTIAL FOR TECHNOLOGICAL INNOVATION This system is unique in capturing botanical recognition knowledge in a hierarchy of neural networks and is the first fully-computerized system for plant identification utilizing information digitized directly from plants. PROPOSED COMMERCIAL APPLICATION 1. Expedite discovery of new medicinal plants for pharmaceutical industry. 2. Create valuable database directly from plants. 3. Identification of poisonous plants. 4. Valuable for rapid identification of invasive weeds.