Studying the distribution characteristics of local flameout using high-speed optical measurement methods is crucial for understanding jet flame instability mechanisms. Initially, a planar laser-induced fluorescence (PLIF) measurement system operating at 5 kHz is set up. An experimental study on high-speed jet flames is conducted with OH-PLIF to monitor the dynamic development of the flame structure. Image processing techniques like bilateral filtering and local adaptive thresholding with vertical sliding windows are then applied to preprocess PLIF images. Innovative features such as the length and spatial location of local fracture structures are extracted. Subsequently, the temporal and spatial distribution characteristics of local flameouts are analyzed, enhancing the high-speed PLIF diagnostic and analytical methods. Results indicate that the bilateral filtering algorithm significantly improves image quality, achieving a peak signal-to-noise ratio of 34.3 dB and a structural similarity index of 0.93. The algorithm effectively reduces noise levels. The F1 score for the adaptive image segmentation method using vertical sliding windows reaches 93.30%. Moreover, the count of fractured structures linearly increases over time. As the jet Mach number rises from 0.5 to 1.6, the number of fractured structures per second in the unilateral image jumps from 790.7 to 9 217.2, showing an exponential relationship with the jet Mach number. Predominant areas for fracture structures include the flame arms and the upper central fuel zone. This research validates the effectiveness of high-speed PLIF technology in assessing the spatial and temporal distribution of local flameout, broadening its potential applications.