@article{MAKHILLJEAS2018132016987,
    title = {An Intelligent Image Classifier Based on Histogram of Oriented Gradients Features},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {20},
    pages = {8506-8510},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.8506.8510},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.8506.8510},
    author = {Methaq and},
    keywords = {Image classification,feature extraction,ANN,(HOG),extract vector,high accuracy},
    abstract = {This study presents an intelligent classifier for images classification based on Artificial Neural
Network (ANN). The Histogram of Oriented Gradients (HOG) techinque has been used in order to extract
features from image. The ANN supervised feed-forward scaled conjugate gradient algorithm used to bulid the
proposed classifier. The input image is processed directly to extract vector features regardless of size or colour
map. The architecture of ANN is selected to be simple and appropriate to carry out the classification process
with high accuracy. This work is performed on the Caltech dataset. Four classes of image are used to test and
evaluate the performance of the proposed classifier (96 images for all category), the testing images consists of
192 images (48 images for each category). Experimental results showed that the classification rate was 93.23%.}
    }