The document discusses object detection in images, highlighting its significance in computer vision and image processing. It details the tools used, including OpenCV, DNN, and SSD frameworks, and describes a project that detects multiple objects within images using these technologies. Applications of the project include face detection, people counting, vehicle detection, and security enhancements.

1. OBJECT
DETECTION
IN IMAGE
Presented By:
ROUSHAN KUMAR
SARWAJEET BHARTI

2. CONTENTS
 INTORDUCTION
 TOOLS USED
 DESCRIPTION OF PROJECT
 EXPERIMENTAL RESULTS
 APPLICATION

3. INTRODUCTION
 OBJECT DETECTION IS COMPUTER TECHNOLOGY REALATED TO COMPUTER VISION
AND IMAGE PROCESSING
 IT IS USED IN OBJECT DETECTION IN IMAGE
 OBJECT DETECTION IS DIFFERENT FROM OBJECT RECOGNITION
 OBJECTION DETECTION NOT ONLY RECOGNIZES OBJECT AND ALSO TELL US THE
POSITION WHERE OBJECTS ARE PRESENT IN THE IMAGE.
 IT USES DNN MODULE AND CAFFE FRAME WORK FOR TRANING IMAGE

4. TOOLS USED
 OPENCV 3.3.0
 DNN(DEEP NEURAL NETWORK)
 MOBILENET ARCHITECTURE
 SSD(SINGLE SHOT DETECTOR) FRAMEWORK
 CAFFE (DEEP LEARNING FRAMEWORK)
 COCO
 PYHTON LANGUAGE

5. DESCRIPTION OF PROJECT
 UPLOAD REQUIRED IMAGE
 UPLOAD DNN MODULE AND CAFFE FRAMEWORK
 USE THE BONDING BOXEX AROUND THE DETECTED OBJECT
 TAG AND ACCURACY PERCTANGE DISPLAYED ON TOP LEFT
 IT CAN DETECT SEVERAL OBJECT WHICH IS TRAINED UNDER DNN MODULE
 SEGMENTATION AND DOWNSAMPLING TECHNIQUES USED IN DNN

10. EXPERIMENTAL RESULT

11. APPLICATION
 FACE DETECTION
 PEOPLE COUNTING
 VEHICLE DETECION
 ONLINE IMAGES DETECTION
 SECURITY