Gabor filters are a type of bandpass filter used in image processing and computer vision for tasks like texture analysis, edge detection, and feature extraction. Gabor filters have parameters that control their properties, including kernel size, standard deviation, orientation, wavelength, ellipticity, phase offset, and data type. Applying Gabor filters to handwritten text can extract features for tasks like recognition.

1. GABOR FILTERS
Eng/ Mahmoud Yasser Hammam
Under supervision of Acoss.prof.eng/ Ahmed Rafaat

2. WHAT IS EXACTLY GABOR FILTER
• For image processing and computer vision, Gabor filters are generally used in texture
analysis, edge detection, feature extraction, etc. Gabor filters are special classes of bandpass
filters, i.e., they allow a certain ‘band’ of frequencies and reject the others.

3. WHAT IS GABORKERNEL
FUNCTION PARAMETERS
1- (ksize, ksize): This is a tuple specifying the size of the kernel. ksize is the size of the Gabor
filter. It determines the width and height of the filter.
2- sigma: Sigma (σ) is the standard deviation of the Gaussian envelope used in the Gabor
kernel. It controls the spread of the Gaussian component.
3- theta: Theta (θ) is the orientation of the normal to the parallel stripes of the Gabor function.
It defines the orientation of the filter in radians.

4. WHAT IS GABORKERNEL
FUNCTION PARAMETERS
4- lamda: Lambda (λ) is the wavelength of the sinusoidal factor. It controls the frequency of
the Gabor function.
5- gamma: Gamma (γ) is the spatial aspect ratio. It specifies the ellipticity of the Gaussian
envelope.
6- phi: Phi (φ) is the phase offset. It specifies the phase offset of the sinusoidal factor in the
Gabor function.
7- ktype=cv2.CV_32F: This parameter specifies the data type of the kernel. In this case, it's set
to cv2.CV_32F, which indicates a 32-bit floating-point type.

5. AFTER APPLYTING GABOR FILTER ON
HANDWRITTEN TEXT