US-12626425-B2 - Wafer image equalization method and apparatus

Abstract

A method for wafer image equalization includes obtaining a wafer image, converting the wafer image into bitmap data, generating a grayscale distribution of RGB pixels according to the bitmap data, generating a grayscale cumulative probability distribution of the RGB pixels according to the grayscale distribution, generating a mapping function according to the grayscale cumulative probability distribution of the RGB pixels, converting the grayscale distribution of the RGB pixels by the mapping function into an equalized grayscale distribution of the RGB pixels, and generating an equalized wafer image according to the equalized grayscale distribution of the RGB pixels.

Inventors

• Qiao Lin Chen
• Ching-Shu Lo
• Yan Cai
• Tsung Che Lin
• Wen Yi Tan

Assignees

• United Semiconductor (Xiamen) Co., Ltd.

Dates

Publication Date

20260512

Application Date

20230210

Priority Date

20221228

Claims (10)

1. 1 . A method for wafer image equalization comprising: obtaining a wafer image; converting the wafer image into bitmap data comprising RGB pixels; generating a corresponding grayscale distribution for each of a red component, a green component, and a blue component of the RGB pixels according to the bitmap data; generating a corresponding grayscale cumulative probability distribution for each of the red component, the green component, and the blue component of the RGB pixels according to the corresponding grayscale distribution; generating a corresponding mapping function according to the corresponding grayscale cumulative probability distribution for each of the red, green, and blue components of the RGB pixels; converting the corresponding grayscale distribution for each of the red, green, and blue components of the RGB pixels into an equalized grayscale distribution for each of red, green, and blue components of the RGB pixels according to the corresponding mapping function; and generating an equalized wafer image according to the equalized grayscale distribution for each of the red, green, and blue components of the RGB pixels.
2. 2 . The method of claim 1 , wherein the corresponding grayscale distribution for each of the red, green, and blue components of the RGB pixels is generated according to a following equation: h ⁡ ( k ) = n k wherein: h(k) is a grayscale distribution function; n k is number of pixels with a grayscale value of k; and k is an integer between 0 and 255.
3. 3 . The method of claim 2 , wherein the corresponding grayscale cumulative probability distribution for each of the red, green, and blue components of the RGB pixels is generated according to a following equation: P ⁡ ( k ) = ∑ i = 0 k n i N wherein: P(k) is a grayscale cumulative probability distribution function; N is total number of pixels; and n i is number of pixels with grayscale value of i.
4. 4 . The method of claim 3 , wherein the corresponding mapping function is generated according to a following equation: s ⁡ ( k ) = P ⁡ ( k ) × 2 ⁢ 5 ⁢ 5 wherein: s(k) is the mapping function.
5. 5 . The method of claim 4 , wherein converting the corresponding grayscale distribution for each of the red, green, and blue components of the RGB pixels into the equalized grayscale distribution of the RGB pixels according to the corresponding mapping function is according to a following equation: h e ( k ) = s ⁡ ( k ) wherein: h e (k) is an equalized grayscale distribution function.
6. 6 . The method of claim 1 , wherein obtaining the wafer image comprises: using a wafer intelligent scanner to capture a raw wafer image; and decoding the raw wafer image to generate the wafer image.
7. 7 . The method of claim 6 , wherein obtaining the wafer image further comprises obtaining a height and a width of the raw wafer image.
8. 8 . The method of claim 1 , wherein the bitmap data comprises a position of each of the RGB pixels.
9. 9 . A wafer image equalization apparatus comprising: a wafer intelligent scanner for capturing a raw wafer image; and a processor coupled to the wafer intelligent scanner, configured to: decode the raw wafer image to generate the wafer image; convert the wafer image into bitmap data comprising RGB pixels; generate a corresponding grayscale distribution for each of a red component, a green component, and a blue component of the RGB pixels according to the bitmap data; generate a corresponding grayscale cumulative probability distribution for each of the red, green, and blue components of the RGB pixels according to the corresponding grayscale distribution; generate a corresponding mapping function according to the corresponding grayscale cumulative probability distribution for each of the red, green, and blue components of the RGB pixels; convert the corresponding grayscale distribution for each of the red, green, and blue components of the RGB pixels into an equalized grayscale distribution for each of the red, green, and blue components of the RGB pixels according to the corresponding mapping function; and generate an equalized wafer image according to the equalized grayscale distribution for each of the red, green, and blue components of the RGB pixels.
10. 10 . The wafer image equalization apparatus of claim 9 , wherein the bitmap data comprises a position of each of the RGB pixels.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention is related to wafer image processing, and more particular to a wafer image equalization method and apparatus. 2. Description of the Prior Art A wafer intelligence scanner is an essential part of the wafer inspection. The machine integrates optical and visual technology with multi-angle illumination sources to obtain images of wafer with its defects. The wafer intelligence scanner can be widely used in the detection of various wafer defects such as crack, scratches, discoloring, feature loss, shift, deformation and foreign particle, etc. However, wafer engineers often need to manually inspect wafer images obtained by wafer scanners to confirm wafer status. With typical wafer image color distributions, image features of wafer defects often blend into the background. When this happens, wafer engineers may miss some wafer defects and waste a lot of time manually finding wafer defects. However, wafer images can be converted to digital data and optimized by image processing techniques. Therefore, image processing methods are helpful to engineers for them to quickly find wafer defects. SUMMARY OF THE INVENTION An embodiment provides a method for wafer image equalization. The method includes obtaining a wafer image, converting the wafer image into bitmap data, generating a grayscale distribution of RGB pixels according to the bitmap data, generating a grayscale cumulative probability distribution of the RGB pixels according to the grayscale distribution, generating a mapping function according to the grayscale cumulative probability distribution of the RGB pixels, converting the grayscale distribution of the RGB pixels by the mapping function into an equalized grayscale distribution of the RGB pixels, and generating an equalized wafer image according to the equalized grayscale distribution of the RGB pixels. An embodiment provides a wafer image equalization apparatus. The apparatus includes a wafer intelligent scanner for capturing a raw wafer image, and a processor coupled to the wafer intelligent scanner. The processor is used to decode the raw wafer image to generate the wafer image, convert the wafer image into bitmap data, generate a grayscale distribution of RGB pixels according to the bitmap data, generate a grayscale cumulative probability distribution of the RGB pixels according to the grayscale distribution, generate a mapping function according to the grayscale cumulative probability distribution of the RGB pixels, convert the grayscale distribution of the RGB pixels by the mapping function into an equalized grayscale distribution of the RGB pixels, and generate an equalized wafer image according to the equalized grayscale distribution of the RGB pixels. These and other objectives of the present invention will no doubt become obvious to those of ordinary skill in the art after reading the following detailed description of the preferred embodiment that is illustrated in the various figures and drawings. BRIEF DESCRIPTION OF THE DRAWINGS The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing (s) will be provided by the Office upon request and payment of the necessary fee. FIG. 1 is a diagram of a wafer image equalization apparatus of an embodiment. FIG. 2 is an image of a wafer obtained by the wafer intelligent scanner. FIG. 3 is a flowchart of an image equalization method for the image of the wafer of FIG. 2. FIG. 4 is a diagram of grayscale distribution of RGB pixels of the bitmap data of the wafer of FIG. 2. FIG. 5 illustrates the grayscale cumulative probability distribution of red pixels in the image of the wafer of FIG. 2. FIG. 6 illustrates the mapping function of the red pixel of the image of the wafer of FIG. 2. FIG. 7 is a diagram of equalized grayscale distribution of the RGB pixels of the image of the wafer of FIG. 2. FIG. 8 is an equalized image of the wafer of FIG. 2. DETAILED DESCRIPTION FIG. 1 is a diagram of a wafer image equalization apparatus 100 of an embodiment. The wafer image equalization apparatus 100 includes a wafer intelligent scanner 10 and a processor 20 coupled to the wafer intelligent scanner 10. The wafer intelligent scanner 10 is a machine that integrates optical and visual technologies, and obtains wafer images with multi-angle light sources. The wafer intelligent scanner 10 can detect physical defects and pattern defects on wafers and obtain the position coordinates. Defects can be divided into random defects and systematic defects. Random defects are mainly caused by particles that become attached to a wafer surface, so their positions cannot be predicted. Systematic defects are caused by the conditions of the mask and exposure process, and will occur in the same position on the circuit pattern of all the dies projected. They occur in locations where the exposure conditions are very difficult and r