TY  - JOUR
T1  - Local Quadrant Pattern with Co-occurrence Matrix (LQP-CM): Hybrid Method for
Image Classification and Feature Extraction
AU - Mahdi Al-Jawahry, Hassan Mohammed AU - Rustum Mohammed, Hind 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 7
SP  - 2171
EP  - 2176
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.2171.2176
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.2171.2176
KW  - Local quadrant pattern
KW  -local quadrant pattern with co-occurrence matrix
KW  -local binary pattern
KW  -local
ternary pattern
KW  -gray-level co-occurrence matrix
KW  -classification
KW  -Euclidean distance
AB  - Image classification is important in several fields which depend on the methods of extracting
the features. This study proposes a new method for features extraction called Local Quadrant Pattern with
Co-occurrence Matrix (LQP-CM) that related with Local Ternary Pattern (LTP) and Gray-Level Co-occurrence
Matrix (GLCM). LQP-CM will map the values into four types instead of two like Local Binary Pattern (LBP) or
three like LTP. For classification, this study will use the Euclidean Distance (ED) to classifying the features that
extracting. The data set that used in this study is Brodatz dataset. The MATLAB environment was adopted
in the programming and the criteria was used to evaluate the performance of the proposed method is percentage
of correct classification which proved successful in classification the database used in high efficiency.
ER  -