image processing

A: Data Collection.

1- Dataset collection: Collect hundreds of grayscale images (200 hundred is the minimum). The dataset should include a least 4 categories. (e.g cars, horses, buildings, tigers…).

The categories should be balanced (approximately the same number of images for each category).

2- Dataset labeling:

a. Assign a Label to each image. (E.g. For car image assign 1, horse 2, building 3 and tiger 4…).

b. After ordering your images, construct a vector containing the label of each image in same order of the images.

c. Save all images in a directory called ImagesDatayourNamed. Save the list of the image names ordred and its corresponding labeling vector in [url removed, login to view] and [url removed, login to view] files.

3- If needed, enhance or/and restore the images. Explain why it is need and the choice of the performed method.

B: Feature Extraction:

1- For each image from the image Data, extract at least one color feature.

2- Normalize you data. For each Feature, make each entry between 0 and 1 for all images.

3- Save each Feature in an MxN matrix where M is the number of images and N is the dimension of your Feature vector. You have to use the same order of the images as the one in your name and label files

4- Write a Readme File that describes each Feature used, indicates the corresponding name of the Feature file, and the name of the Matlab function that extract it.

C: Retrieval:

1. Query Image Q (Selection and display): Select and display the query image.

2. Retrieved image Rank 1, 2,3 and 4: Display the resulting retrieved image.

3. Dist(Q,R1), Dist(Q,R2), Dist(Q,R3), Dist(Q,R4): display the distance between the query and the retrieved image under the retrieved one.

4. Score of this retrieval: evaluates the current [url removed, login to view] Report:-The final report should roughly have the following format:

 Introduction - Motivation

 Problem definition Proposed method

 Experimentso Details of the experiments; observations

 Conclusions


- you need to change all the images that to collect to grayscale before you start working.

Habilidades: Matlab and Mathematica

Veja mais: method to write a report, dimension data, definition of data entry, data entry definition, image of tiger, Tigers, MATLAB image, labeling, image processing, distance vector, data collection needed, car processing, horse images, include restore feature, restore needed, image car, use extract function, image query, image collect, data normalize, introduction data entry, data entry data processing image processing work, data entry introduction, order retrieval, image feature extraction

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